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Oligonucleotide Array Sequence AnalysisOligonucleotide ProbesGene Expression ProfilingSequence Analysis, DNAOligonucleotidesBase SequenceMolecular Sequence DataNucleic Acid HybridizationDNA ProbesComparative Genomic HybridizationPolymerase Chain ReactionAmino Acid SequenceReproducibility of ResultsDNA, Ribosomal SpacerGene DosageRNA, MessengerReverse Transcriptase Polymerase Chain ReactionSensitivity and SpecificityCluster AnalysisDNAAlgorithmsDNA, BacterialCloning, MolecularOligonucleotides, AntisenseGenome, HumanSequence AnalysisRNATranscription, GeneticGene Expression RegulationDNA PrimersPhylogenyChromosome MappingSpecies SpecificityGene ExpressionChromosomes, Artificial, BacterialIn Situ Hybridization, FluorescenceRNA, ComplementaryRNA, Ribosomal, 16SGlassSequence Homology, Nucleic AcidMicroarray AnalysisFixativesGene Expression Regulation, NeoplasticDNA, ComplementaryOligodeoxyribonucleotidesExonsMutationGenetic VariationModels, GeneticDNA Copy Number VariationsPolymorphism, Single NucleotideSoftwareDNA, RibosomalMultigene FamilyComputational BiologyGenomicsGenotypeNucleic Acid Amplification TechniquesExpressed Sequence TagsTranscription FactorsModels, StatisticalData Interpretation, StatisticalSequence Homology, Amino AcidRNA, NeoplasmGenes, NeoplasmChromosome AberrationsGenes, BacterialSequence AlignmentAllelesDNA-Binding ProteinsBlotting, NorthernReference StandardsRestriction MappingCell LineDNA Mutational AnalysisGene DeletionPhenotypePromoter Regions, GeneticGenomeOligoribonucleotidesDatabases, GeneticCelastraceaeUp-RegulationEscherichia coliBase CompositionGenome, PlantGene DuplicationNucleic Acid ConformationCell Line, TumorTumor Cells, CulturedBacterial ProteinsRNA, BacterialAptitudePlasmidsComputer SimulationProteinsDNA, NeoplasmPhosphorothioate OligonucleotidesOpen Reading FramesOligodeoxyribonucleotides, AntisenseProtein Array AnalysisSignal TransductionNeoplasm ProteinsGenesGene LibraryCells, CulturedBlotting, SouthernGenes, rRNABinding SitesDown-RegulationBacterial Typing TechniquesSequence Analysis, ProteinTime FactorsRepetitive Sequences, Nucleic AcidDNA, ViralThionucleotidesElectrophoresis, Polyacrylamide GelDNA Restriction EnzymesApoptosisDNA, FungalRNA, ViralOligoribonucleotides, AntisenseMice, Inbred C57BLMolecular WeightConserved SequenceCodonGenes, ViralRecombinant ProteinsSequence HomologyKineticsPolymorphism, Restriction Fragment LengthSequence Analysis, RNACattleMolecular Probe TechniquesNucleic Acid DenaturationSubstrate SpecificitySoil MicrobiologyBacteriaDNA Transposable ElementsRNA, RibosomalGenome, ViralChromatography, High Pressure LiquidEvolution, MolecularProtein BindingConsensus SequenceIntrons
Oligonucleotide Array Sequence Analysis: Hybridization of a nucleic acid sample to a very large set of OLIGONUCLEOTIDE PROBES, which have been attached individually in columns and rows to a solid support, to determine a BASE SEQUENCE, or to detect variations in a gene sequence, GENE EXPRESSION, or for GENE MAPPING.Oligonucleotide Probes: Synthetic or natural oligonucleotides used in hybridization studies in order to identify and study specific nucleic acid fragments, e.g., DNA segments near or within a specific gene locus or gene. The probe hybridizes with a specific mRNA, if present. Conventional techniques used for testing for the hybridization product include dot blot assays, Southern blot assays, and DNA:RNA hybrid-specific antibody tests. Conventional labels for the probe include the radioisotope labels 32P and 125I and the chemical label biotin.Gene Expression Profiling: The determination of the pattern of genes expressed at the level of GENETIC TRANSCRIPTION, under specific circumstances or in a specific cell.Sequence Analysis, DNA: A multistage process that includes cloning, physical mapping, subcloning, determination of the DNA SEQUENCE, and information analysis.Oligonucleotides: Polymers made up of a few (2-20) nucleotides. In molecular genetics, they refer to a short sequence synthesized to match a region where a mutation is known to occur, and then used as a probe (OLIGONUCLEOTIDE PROBES). (Dorland, 28th ed)Base Sequence: The sequence of PURINES and PYRIMIDINES in nucleic acids and polynucleotides. It is also called nucleotide sequence.Molecular Sequence Data: Descriptions of specific amino acid, carbohydrate, or nucleotide sequences which have appeared in the published literature and/or are deposited in and maintained by databanks such as GENBANK, European Molecular Biology Laboratory (EMBL), National Biomedical Research Foundation (NBRF), or other sequence repositories.Nucleic Acid Hybridization: Widely used technique which exploits the ability of complementary sequences in single-stranded DNAs or RNAs to pair with each other to form a double helix. Hybridization can take place between two complimentary DNA sequences, between a single-stranded DNA and a complementary RNA, or between two RNA sequences. The technique is used to detect and isolate specific sequences, measure homology, or define other characteristics of one or both strands. (Kendrew, Encyclopedia of Molecular Biology, 1994, p503)DNA Probes: Species- or subspecies-specific DNA (including COMPLEMENTARY DNA; conserved genes, whole chromosomes, or whole genomes) used in hybridization studies in order to identify microorganisms, to measure DNA-DNA homologies, to group subspecies, etc. The DNA probe hybridizes with a specific mRNA, if present. Conventional techniques used for testing for the hybridization product include dot blot assays, Southern blot assays, and DNA:RNA hybrid-specific antibody tests. Conventional labels for the DNA probe include the radioisotope labels 32P and 125I and the chemical label biotin. The use of DNA probes provides a specific, sensitive, rapid, and inexpensive replacement for cell culture techniques for diagnosing infections.Comparative Genomic Hybridization: A method for comparing two sets of chromosomal DNA by analyzing differences in the copy number and location of specific sequences. It is used to look for large sequence changes such as deletions, duplications, amplifications, or translocations.Polymerase Chain Reaction: In vitro method for producing large amounts of specific DNA or RNA fragments of defined length and sequence from small amounts of short oligonucleotide flanking sequences (primers). The essential steps include thermal denaturation of the double-stranded target molecules, annealing of the primers to their complementary sequences, and extension of the annealed primers by enzymatic synthesis with DNA polymerase. The reaction is efficient, specific, and extremely sensitive. Uses for the reaction include disease diagnosis, detection of difficult-to-isolate pathogens, mutation analysis, genetic testing, DNA sequencing, and analyzing evolutionary relationships.Amino Acid Sequence: The order of amino acids as they occur in a polypeptide chain. This is referred to as the primary structure of proteins. It is of fundamental importance in determining PROTEIN CONFORMATION.Reproducibility of Results: The statistical reproducibility of measurements (often in a clinical context), including the testing of instrumentation or techniques to obtain reproducible results. The concept includes reproducibility of physiological measurements, which may be used to develop rules to assess probability or prognosis, or response to a stimulus; reproducibility of occurrence of a condition; and reproducibility of experimental results.DNA, Ribosomal Spacer: The intergenic DNA segments that are between the ribosomal RNA genes (internal transcribed spacers) and between the tandemly repeated units of rDNA (external transcribed spacers and nontranscribed spacers).Gene Dosage: The number of copies of a given gene present in the cell of an organism. An increase in gene dosage (by GENE DUPLICATION for example) can result in higher levels of gene product formation. GENE DOSAGE COMPENSATION mechanisms result in adjustments to the level GENE EXPRESSION when there are changes or differences in gene dosage.RNA, Messenger: RNA sequences that serve as templates for protein synthesis. Bacterial mRNAs are generally primary transcripts in that they do not require post-transcriptional processing. Eukaryotic mRNA is synthesized in the nucleus and must be exported to the cytoplasm for translation. Most eukaryotic mRNAs have a sequence of polyadenylic acid at the 3' end, referred to as the poly(A) tail. The function of this tail is not known for certain, but it may play a role in the export of mature mRNA from the nucleus as well as in helping stabilize some mRNA molecules by retarding their degradation in the cytoplasm.Reverse Transcriptase Polymerase Chain Reaction: A variation of the PCR technique in which cDNA is made from RNA via reverse transcription. The resultant cDNA is then amplified using standard PCR protocols.Sensitivity and Specificity: Binary classification measures to assess test results. Sensitivity or recall rate is the proportion of true positives. Specificity is the probability of correctly determining the absence of a condition. (From Last, Dictionary of Epidemiology, 2d ed)Cluster Analysis: A set of statistical methods used to group variables or observations into strongly inter-related subgroups. In epidemiology, it may be used to analyze a closely grouped series of events or cases of disease or other health-related phenomenon with well-defined distribution patterns in relation to time or place or both.DNA: A deoxyribonucleotide polymer that is the primary genetic material of all cells. Eukaryotic and prokaryotic organisms normally contain DNA in a double-stranded state, yet several important biological processes transiently involve single-stranded regions. DNA, which consists of a polysugar-phosphate backbone possessing projections of purines (adenine and guanine) and pyrimidines (thymine and cytosine), forms a double helix that is held together by hydrogen bonds between these purines and pyrimidines (adenine to thymine and guanine to cytosine).Algorithms: A procedure consisting of a sequence of algebraic formulas and/or logical steps to calculate or determine a given task.DNA, Bacterial: Deoxyribonucleic acid that makes up the genetic material of bacteria.Cloning, Molecular: The insertion of recombinant DNA molecules from prokaryotic and/or eukaryotic sources into a replicating vehicle, such as a plasmid or virus vector, and the introduction of the resultant hybrid molecules into recipient cells without altering the viability of those cells.Oligonucleotides, Antisense: Short fragments of DNA or RNA that are used to alter the function of target RNAs or DNAs to which they hybridize.Genome, Human: The complete genetic complement contained in the DNA of a set of CHROMOSOMES in a HUMAN. The length of the human genome is about 3 billion base pairs.Sequence Analysis: A multistage process that includes the determination of a sequence (protein, carbohydrate, etc.), its fragmentation and analysis, and the interpretation of the resulting sequence information.RNA: A polynucleotide consisting essentially of chains with a repeating backbone of phosphate and ribose units to which nitrogenous bases are attached. RNA is unique among biological macromolecules in that it can encode genetic information, serve as an abundant structural component of cells, and also possesses catalytic activity. (Rieger et al., Glossary of Genetics: Classical and Molecular, 5th ed)Transcription, Genetic: The biosynthesis of RNA carried out on a template of DNA. The biosynthesis of DNA from an RNA template is called REVERSE TRANSCRIPTION.Gene Expression Regulation: Any of the processes by which nuclear, cytoplasmic, or intercellular factors influence the differential control (induction or repression) of gene action at the level of transcription or translation.DNA Primers: Short sequences (generally about 10 base pairs) of DNA that are complementary to sequences of messenger RNA and allow reverse transcriptases to start copying the adjacent sequences of mRNA. Primers are used extensively in genetic and molecular biology techniques.Phylogeny: The relationships of groups of organisms as reflected by their genetic makeup.Chromosome Mapping: Any method used for determining the location of and relative distances between genes on a chromosome.Species Specificity: The restriction of a characteristic behavior, anatomical structure or physical system, such as immune response; metabolic response, or gene or gene variant to the members of one species. It refers to that property which differentiates one species from another but it is also used for phylogenetic levels higher or lower than the species.Gene Expression: The phenotypic manifestation of a gene or genes by the processes of GENETIC TRANSCRIPTION and GENETIC TRANSLATION.Chromosomes, Artificial, Bacterial: DNA constructs that are composed of, at least, a REPLICATION ORIGIN, for successful replication, propagation to and maintenance as an extra chromosome in bacteria. In addition, they can carry large amounts (about 200 kilobases) of other sequence for a variety of bioengineering purposes.In Situ Hybridization, Fluorescence: A type of IN SITU HYBRIDIZATION in which target sequences are stained with fluorescent dye so their location and size can be determined using fluorescence microscopy. This staining is sufficiently distinct that the hybridization signal can be seen both in metaphase spreads and in interphase nuclei.RNA, Complementary: Synthetic transcripts of a specific DNA molecule or fragment, made by an in vitro transcription system. This cRNA can be labeled with radioactive uracil and then used as a probe. (King & Stansfield, A Dictionary of Genetics, 4th ed)RNA, Ribosomal, 16S: Constituent of 30S subunit prokaryotic ribosomes containing 1600 nucleotides and 21 proteins. 16S rRNA is involved in initiation of polypeptide synthesis.Glass: Hard, amorphous, brittle, inorganic, usually transparent, polymerous silicate of basic oxides, usually potassium or sodium. It is used in the form of hard sheets, vessels, tubing, fibers, ceramics, beads, etc.Sequence Homology, Nucleic Acid: The sequential correspondence of nucleotides in one nucleic acid molecule with those of another nucleic acid molecule. Sequence homology is an indication of the genetic relatedness of different organisms and gene function.Microarray Analysis: The simultaneous analysis, on a microchip, of multiple samples or targets arranged in an array format.Fixatives: Agents employed in the preparation of histologic or pathologic specimens for the purpose of maintaining the existing form and structure of all of the constituent elements. Great numbers of different agents are used; some are also decalcifying and hardening agents. They must quickly kill and coagulate living tissue.Gene Expression Regulation, Neoplastic: Any of the processes by which nuclear, cytoplasmic, or intercellular factors influence the differential control of gene action in neoplastic tissue.DNA, Complementary: Single-stranded complementary DNA synthesized from an RNA template by the action of RNA-dependent DNA polymerase. cDNA (i.e., complementary DNA, not circular DNA, not C-DNA) is used in a variety of molecular cloning experiments as well as serving as a specific hybridization probe.Oligodeoxyribonucleotides: A group of deoxyribonucleotides (up to 12) in which the phosphate residues of each deoxyribonucleotide act as bridges in forming diester linkages between the deoxyribose moieties.Exons: The parts of a transcript of a split GENE remaining after the INTRONS are removed. They are spliced together to become a MESSENGER RNA or other functional RNA.Mutation: Any detectable and heritable change in the genetic material that causes a change in the GENOTYPE and which is transmitted to daughter cells and to succeeding generations.Genetic Variation: Genotypic differences observed among individuals in a population.Models, Genetic: Theoretical representations that simulate the behavior or activity of genetic processes or phenomena. They include the use of mathematical equations, computers, and other electronic equipment.DNA Copy Number Variations: Stretches of genomic DNA that exist in different multiples between individuals. Many copy number variations have been associated with susceptibility or resistance to disease.Polymorphism, Single Nucleotide: A single nucleotide variation in a genetic sequence that occurs at appreciable frequency in the population.Software: Sequential operating programs and data which instruct the functioning of a digital computer.DNA, Ribosomal: DNA sequences encoding RIBOSOMAL RNA and the segments of DNA separating the individual ribosomal RNA genes, referred to as RIBOSOMAL SPACER DNA.Multigene Family: A set of genes descended by duplication and variation from some ancestral gene. Such genes may be clustered together on the same chromosome or dispersed on different chromosomes. Examples of multigene families include those that encode the hemoglobins, immunoglobulins, histocompatibility antigens, actins, tubulins, keratins, collagens, heat shock proteins, salivary glue proteins, chorion proteins, cuticle proteins, yolk proteins, and phaseolins, as well as histones, ribosomal RNA, and transfer RNA genes. The latter three are examples of reiterated genes, where hundreds of identical genes are present in a tandem array. (King & Stanfield, A Dictionary of Genetics, 4th ed)Computational Biology: A field of biology concerned with the development of techniques for the collection and manipulation of biological data, and the use of such data to make biological discoveries or predictions. This field encompasses all computational methods and theories for solving biological problems including manipulation of models and datasets.Genomics: The systematic study of the complete DNA sequences (GENOME) of organisms.Genotype: The genetic constitution of the individual, comprising the ALLELES present at each GENETIC LOCUS.Nucleic Acid Amplification Techniques: Laboratory techniques that involve the in-vitro synthesis of many copies of DNA or RNA from one original template.Expressed Sequence Tags: Partial cDNA (DNA, COMPLEMENTARY) sequences that are unique to the cDNAs from which they were derived.Transcription Factors: Endogenous substances, usually proteins, which are effective in the initiation, stimulation, or termination of the genetic transcription process.Models, Statistical: Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc.Data Interpretation, Statistical: Application of statistical procedures to analyze specific observed or assumed facts from a particular study.Sequence Homology, Amino Acid: The degree of similarity between sequences of amino acids. This information is useful for the analyzing genetic relatedness of proteins and species.RNA, Neoplasm: RNA present in neoplastic tissue.Genes, Neoplasm: Genes whose abnormal expression, or MUTATION are associated with the development, growth, or progression of NEOPLASMS.Chromosome Aberrations: Abnormal number or structure of chromosomes. Chromosome aberrations may result in CHROMOSOME DISORDERS.Genes, Bacterial: The functional hereditary units of BACTERIA.Sequence Alignment: The arrangement of two or more amino acid or base sequences from an organism or organisms in such a way as to align areas of the sequences sharing common properties. The degree of relatedness or homology between the sequences is predicted computationally or statistically based on weights assigned to the elements aligned between the sequences. This in turn can serve as a potential indicator of the genetic relatedness between the organisms.Alleles: Variant forms of the same gene, occupying the same locus on homologous CHROMOSOMES, and governing the variants in production of the same gene product.DNA-Binding Proteins: Proteins which bind to DNA. The family includes proteins which bind to both double- and single-stranded DNA and also includes specific DNA binding proteins in serum which can be used as markers for malignant diseases.Blotting, Northern: Detection of RNA that has been electrophoretically separated and immobilized by blotting on nitrocellulose or other type of paper or nylon membrane followed by hybridization with labeled NUCLEIC ACID PROBES.Reference Standards: A basis of value established for the measure of quantity, weight, extent or quality, e.g. weight standards, standard solutions, methods, techniques, and procedures used in diagnosis and therapy.Restriction Mapping: Use of restriction endonucleases to analyze and generate a physical map of genomes, genes, or other segments of DNA.Cell Line: Established cell cultures that have the potential to propagate indefinitely.DNA Mutational Analysis: Biochemical identification of mutational changes in a nucleotide sequence.Gene Deletion: A genetic rearrangement through loss of segments of DNA or RNA, bringing sequences which are normally separated into close proximity. This deletion may be detected using cytogenetic techniques and can also be inferred from the phenotype, indicating a deletion at one specific locus.Phenotype: The outward appearance of the individual. It is the product of interactions between genes, and between the GENOTYPE and the environment.Promoter Regions, Genetic: DNA sequences which are recognized (directly or indirectly) and bound by a DNA-dependent RNA polymerase during the initiation of transcription. Highly conserved sequences within the promoter include the Pribnow box in bacteria and the TATA BOX in eukaryotes.Genome: The genetic complement of an organism, including all of its GENES, as represented in its DNA, or in some cases, its RNA.Oligoribonucleotides: A group of ribonucleotides (up to 12) in which the phosphate residues of each ribonucleotide act as bridges in forming diester linkages between the ribose moieties.Databases, Genetic: Databases devoted to knowledge about specific genes and gene products.Celastraceae: A plant family of the order Celastrales, subclass Rosidae, class Magnoliopsida.Up-Regulation: A positive regulatory effect on physiological processes at the molecular, cellular, or systemic level. At the molecular level, the major regulatory sites include membrane receptors, genes (GENE EXPRESSION REGULATION), mRNAs (RNA, MESSENGER), and proteins.Escherichia coli: A species of gram-negative, facultatively anaerobic, rod-shaped bacteria (GRAM-NEGATIVE FACULTATIVELY ANAEROBIC RODS) commonly found in the lower part of the intestine of warm-blooded animals. It is usually nonpathogenic, but some strains are known to produce DIARRHEA and pyogenic infections. Pathogenic strains (virotypes) are classified by their specific pathogenic mechanisms such as toxins (ENTEROTOXIGENIC ESCHERICHIA COLI), etc.Base Composition: The relative amounts of the PURINES and PYRIMIDINES in a nucleic acid.Genome, Plant: The genetic complement of a plant (PLANTS) as represented in its DNA.Gene Duplication: Processes occurring in various organisms by which new genes are copied. Gene duplication may result in a MULTIGENE FAMILY; supergenes or PSEUDOGENES.Nucleic Acid Conformation: The spatial arrangement of the atoms of a nucleic acid or polynucleotide that results in its characteristic 3-dimensional shape.Cell Line, Tumor: A cell line derived from cultured tumor cells.Tumor Cells, Cultured: Cells grown in vitro from neoplastic tissue. If they can be established as a TUMOR CELL LINE, they can be propagated in cell culture indefinitely.Bacterial Proteins: Proteins found in any species of bacterium.RNA, Bacterial: Ribonucleic acid in bacteria having regulatory and catalytic roles as well as involvement in protein synthesis.Aptitude: The ability to acquire general or special types of knowledge or skill.Plasmids: Extrachromosomal, usually CIRCULAR DNA molecules that are self-replicating and transferable from one organism to another. They are found in a variety of bacterial, archaeal, fungal, algal, and plant species. They are used in GENETIC ENGINEERING as CLONING VECTORS.Computer Simulation: Computer-based representation of physical systems and phenomena such as chemical processes.Proteins: Linear POLYPEPTIDES that are synthesized on RIBOSOMES and may be further modified, crosslinked, cleaved, or assembled into complex proteins with several subunits. The specific sequence of AMINO ACIDS determines the shape the polypeptide will take, during PROTEIN FOLDING, and the function of the protein.DNA, Neoplasm: DNA present in neoplastic tissue.Phosphorothioate Oligonucleotides: Modified oligonucleotides in which one of the oxygens of the phosphate group is replaced with a sulfur atom.Open Reading Frames: A sequence of successive nucleotide triplets that are read as CODONS specifying AMINO ACIDS and begin with an INITIATOR CODON and end with a stop codon (CODON, TERMINATOR).Oligodeoxyribonucleotides, Antisense: Short fragments of DNA that are used to alter the function of target RNAs or DNAs to which they hybridize.Protein Array Analysis: Ligand-binding assays that measure protein-protein, protein-small molecule, or protein-nucleic acid interactions using a very large set of capturing molecules, i.e., those attached separately on a solid support, to measure the presence or interaction of target molecules in the sample.Signal Transduction: The intracellular transfer of information (biological activation/inhibition) through a signal pathway. In each signal transduction system, an activation/inhibition signal from a biologically active molecule (hormone, neurotransmitter) is mediated via the coupling of a receptor/enzyme to a second messenger system or to an ion channel. Signal transduction plays an important role in activating cellular functions, cell differentiation, and cell proliferation. Examples of signal transduction systems are the GAMMA-AMINOBUTYRIC ACID-postsynaptic receptor-calcium ion channel system, the receptor-mediated T-cell activation pathway, and the receptor-mediated activation of phospholipases. Those coupled to membrane depolarization or intracellular release of calcium include the receptor-mediated activation of cytotoxic functions in granulocytes and the synaptic potentiation of protein kinase activation. Some signal transduction pathways may be part of larger signal transduction pathways; for example, protein kinase activation is part of the platelet activation signal pathway.Neoplasm Proteins: Proteins whose abnormal expression (gain or loss) are associated with the development, growth, or progression of NEOPLASMS. Some neoplasm proteins are tumor antigens (ANTIGENS, NEOPLASM), i.e. they induce an immune reaction to their tumor. Many neoplasm proteins have been characterized and are used as tumor markers (BIOMARKERS, TUMOR) when they are detectable in cells and body fluids as monitors for the presence or growth of tumors. Abnormal expression of ONCOGENE PROTEINS is involved in neoplastic transformation, whereas the loss of expression of TUMOR SUPPRESSOR PROTEINS is involved with the loss of growth control and progression of the neoplasm.Genes: A category of nucleic acid sequences that function as units of heredity and which code for the basic instructions for the development, reproduction, and maintenance of organisms.Gene Library: A large collection of DNA fragments cloned (CLONING, MOLECULAR) from a given organism, tissue, organ, or cell type. It may contain complete genomic sequences (GENOMIC LIBRARY) or complementary DNA sequences, the latter being formed from messenger RNA and lacking intron sequences.Cells, Cultured: Cells propagated in vitro in special media conducive to their growth. Cultured cells are used to study developmental, morphologic, metabolic, physiologic, and genetic processes, among others.Blotting, Southern: A method (first developed by E.M. Southern) for detection of DNA that has been electrophoretically separated and immobilized by blotting on nitrocellulose or other type of paper or nylon membrane followed by hybridization with labeled NUCLEIC ACID PROBES.Genes, rRNA: Genes, found in both prokaryotes and eukaryotes, which are transcribed to produce the RNA which is incorporated into RIBOSOMES. Prokaryotic rRNA genes are usually found in OPERONS dispersed throughout the GENOME, whereas eukaryotic rRNA genes are clustered, multicistronic transcriptional units.Binding Sites: The parts of a macromolecule that directly participate in its specific combination with another molecule.Down-Regulation: A negative regulatory effect on physiological processes at the molecular, cellular, or systemic level. At the molecular level, the major regulatory sites include membrane receptors, genes (GENE EXPRESSION REGULATION), mRNAs (RNA, MESSENGER), and proteins.Bacterial Typing Techniques: Procedures for identifying types and strains of bacteria. The most frequently employed typing systems are BACTERIOPHAGE TYPING and SEROTYPING as well as bacteriocin typing and biotyping.Sequence Analysis, Protein: A process that includes the determination of AMINO ACID SEQUENCE of a protein (or peptide, oligopeptide or peptide fragment) and the information analysis of the sequence.Time Factors: Elements of limited time intervals, contributing to particular results or situations.Repetitive Sequences, Nucleic Acid: Sequences of DNA or RNA that occur in multiple copies. There are several types: INTERSPERSED REPETITIVE SEQUENCES are copies of transposable elements (DNA TRANSPOSABLE ELEMENTS or RETROELEMENTS) dispersed throughout the genome. TERMINAL REPEAT SEQUENCES flank both ends of another sequence, for example, the long terminal repeats (LTRs) on RETROVIRUSES. Variations may be direct repeats, those occurring in the same direction, or inverted repeats, those opposite to each other in direction. TANDEM REPEAT SEQUENCES are copies which lie adjacent to each other, direct or inverted (INVERTED REPEAT SEQUENCES).DNA, Viral: Deoxyribonucleic acid that makes up the genetic material of viruses.Thionucleotides: Nucleotides in which the base moiety is substituted with one or more sulfur atoms.Electrophoresis, Polyacrylamide Gel: Electrophoresis in which a polyacrylamide gel is used as the diffusion medium.DNA Restriction Enzymes: Enzymes that are part of the restriction-modification systems. They catalyze the endonucleolytic cleavage of DNA sequences which lack the species-specific methylation pattern in the host cell's DNA. Cleavage yields random or specific double-stranded fragments with terminal 5'-phosphates. The function of restriction enzymes is to destroy any foreign DNA that invades the host cell. Most have been studied in bacterial systems, but a few have been found in eukaryotic organisms. They are also used as tools for the systematic dissection and mapping of chromosomes, in the determination of base sequences of DNAs, and have made it possible to splice and recombine genes from one organism into the genome of another. EC 3.21.1.Apoptosis: One of the mechanisms by which CELL DEATH occurs (compare with NECROSIS and AUTOPHAGOCYTOSIS). Apoptosis is the mechanism responsible for the physiological deletion of cells and appears to be intrinsically programmed. It is characterized by distinctive morphologic changes in the nucleus and cytoplasm, chromatin cleavage at regularly spaced sites, and the endonucleolytic cleavage of genomic DNA; (DNA FRAGMENTATION); at internucleosomal sites. This mode of cell death serves as a balance to mitosis in regulating the size of animal tissues and in mediating pathologic processes associated with tumor growth.DNA, Fungal: Deoxyribonucleic acid that makes up the genetic material of fungi.RNA, Viral: Ribonucleic acid that makes up the genetic material of viruses.Oligoribonucleotides, Antisense: Short fragments of RNA that are used to alter the function of target RNAs or DNAs to which they hybridize.Mice, Inbred C57BLMolecular Weight: The sum of the weight of all the atoms in a molecule.Conserved Sequence: A sequence of amino acids in a polypeptide or of nucleotides in DNA or RNA that is similar across multiple species. A known set of conserved sequences is represented by a CONSENSUS SEQUENCE. AMINO ACID MOTIFS are often composed of conserved sequences.Codon: A set of three nucleotides in a protein coding sequence that specifies individual amino acids or a termination signal (CODON, TERMINATOR). Most codons are universal, but some organisms do not produce the transfer RNAs (RNA, TRANSFER) complementary to all codons. These codons are referred to as unassigned codons (CODONS, NONSENSE).Genes, Viral: The functional hereditary units of VIRUSES.Recombinant Proteins: Proteins prepared by recombinant DNA technology.Sequence Homology: The degree of similarity between sequences. Studies of AMINO ACID SEQUENCE HOMOLOGY and NUCLEIC ACID SEQUENCE HOMOLOGY provide useful information about the genetic relatedness of genes, gene products, and species.Kinetics: The rate dynamics in chemical or physical systems.Polymorphism, Restriction Fragment Length: Variation occurring within a species in the presence or length of DNA fragment generated by a specific endonuclease at a specific site in the genome. Such variations are generated by mutations that create or abolish recognition sites for these enzymes or change the length of the fragment.Sequence Analysis, RNA: A multistage process that includes cloning, physical mapping, subcloning, sequencing, and information analysis of an RNA SEQUENCE.Cattle: Domesticated bovine animals of the genus Bos, usually kept on a farm or ranch and used for the production of meat or dairy products or for heavy labor.Molecular Probe Techniques: The use of devices which use detector molecules to detect, investigate, or analyze other molecules, macromolecules, molecular aggregates, or organisms.Nucleic Acid Denaturation: Disruption of the secondary structure of nucleic acids by heat, extreme pH or chemical treatment. Double strand DNA is "melted" by dissociation of the non-covalent hydrogen bonds and hydrophobic interactions. Denatured DNA appears to be a single-stranded flexible structure. The effects of denaturation on RNA are similar though less pronounced and largely reversible.Substrate Specificity: A characteristic feature of enzyme activity in relation to the kind of substrate on which the enzyme or catalytic molecule reacts.Soil Microbiology: The presence of bacteria, viruses, and fungi in the soil. This term is not restricted to pathogenic organisms.Bacteria: One of the three domains of life (the others being Eukarya and ARCHAEA), also called Eubacteria. They are unicellular prokaryotic microorganisms which generally possess rigid cell walls, multiply by cell division, and exhibit three principal forms: round or coccal, rodlike or bacillary, and spiral or spirochetal. Bacteria can be classified by their response to OXYGEN: aerobic, anaerobic, or facultatively anaerobic; by the mode by which they obtain their energy: chemotrophy (via chemical reaction) or PHOTOTROPHY (via light reaction); for chemotrophs by their source of chemical energy: CHEMOLITHOTROPHY (from inorganic compounds) or chemoorganotrophy (from organic compounds); and by their source for CARBON; NITROGEN; etc.; HETEROTROPHY (from organic sources) or AUTOTROPHY (from CARBON DIOXIDE). They can also be classified by whether or not they stain (based on the structure of their CELL WALLS) with CRYSTAL VIOLET dye: gram-negative or gram-positive.DNA Transposable Elements: Discrete segments of DNA which can excise and reintegrate to another site in the genome. Most are inactive, i.e., have not been found to exist outside the integrated state. DNA transposable elements include bacterial IS (insertion sequence) elements, Tn elements, the maize controlling elements Ac and Ds, Drosophila P, gypsy, and pogo elements, the human Tigger elements and the Tc and mariner elements which are found throughout the animal kingdom.RNA, Ribosomal: The most abundant form of RNA. Together with proteins, it forms the ribosomes, playing a structural role and also a role in ribosomal binding of mRNA and tRNAs. Individual chains are conventionally designated by their sedimentation coefficients. In eukaryotes, four large chains exist, synthesized in the nucleolus and constituting about 50% of the ribosome. (Dorland, 28th ed)Genome, Viral: The complete genetic complement contained in a DNA or RNA molecule in a virus.Chromatography, High Pressure Liquid: Liquid chromatographic techniques which feature high inlet pressures, high sensitivity, and high speed.Evolution, Molecular: The process of cumulative change at the level of DNA; RNA; and PROTEINS, over successive generations.Protein Binding: The process in which substances, either endogenous or exogenous, bind to proteins, peptides, enzymes, protein precursors, or allied compounds. Specific protein-binding measures are often used as assays in diagnostic assessments.Consensus Sequence: A theoretical representative nucleotide or amino acid sequence in which each nucleotide or amino acid is the one which occurs most frequently at that site in the different sequences which occur in nature. The phrase also refers to an actual sequence which approximates the theoretical consensus. A known CONSERVED SEQUENCE set is represented by a consensus sequence. Commonly observed supersecondary protein structures (AMINO ACID MOTIFS) are often formed by conserved sequences.Introns: Sequences of DNA in the genes that are located between the EXONS. They are transcribed along with the exons but are removed from the primary gene transcript by RNA SPLICING to leave mature RNA. Some introns code for separate genes.

A novel method for determining linkage between DNA sequences: hybridization to paired probe arrays. (1/28523)

Cooperative hybridization has been used to establish physical linkage between two loci on a DNA strand. Linkage was detected by hybridization to a new type of high-density oligonucleotide array. Each synthesis location on the array contains a mixture of two different probe sequences. Each of the two probes can hybridize independently to a different target sequence, but if the two target sequences are physically linked there is a cooperative increase in hybridization yield. The ability to create and control non-linear effects raises a host of possibilities for applications of oligonucleotide array hybridization. The method has been used to assign linkage in 50:50 mixtures of DNA containing single nucleotide polymorphisms (SNPs) separated by 17, 693, 1350 and 2038 bp and to reconstruct haplotypes. Other potential uses include increasing the specificity of hybridization in mutation detection and gene expression monitoring applications, determining SNP haplotypes, characterizing repetitive sequences, such as short tandem repeats, and aiding contig assembly in sequen-cing by hybridization.  (+info)

Smoothing of the thermal stability of DNA duplexes by using modified nucleosides and chaotropic agents. (2/28523)

The effect of alkyltrimethylammonium ions on the thermostability of natural and modified DNA duplexes has been investigated. We have shown that the use of tetramethylammonium ions TMA+along with the chemical modification of duplexes allow the fine adjustment of T m and the possibility of obtaining several duplex systems with varied isostabilizedtemperatures, some of which show greater stability than those of natural DNA. This approach could be very useful for DNA sequencing by hybridization.  (+info)

Combining SSH and cDNA microarrays for rapid identification of differentially expressed genes. (3/28523)

Comparing patterns of gene expression in cell lines and tissues has important applications in a variety of biological systems. In this study we have examined whether the emerging technology of cDNA microarrays will allow a high throughput analysis of expression of cDNA clones generated by suppression subtractive hybridization (SSH). A set of cDNA clones including 332 SSH inserts amplified by PCR was arrayed using robotic printing. The cDNA arrays were hybridized with fluorescent labeled probes prepared from RNA from ER-positive (MCF7 and T47D) and ER-negative (MDA-MB-231 and HBL-100) breast cancer cell lines. Ten clones were identified that were over-expressed by at least a factor of five in the ER-positive cell lines. Northern blot analysis confirmed over-expression of these 10 cDNAs. Sequence analysis identified four of these clones as cytokeratin 19, GATA-3, CD24 and glutathione-S-transferase mu-3. Of the remaining six cDNA clones, four clones matched EST sequences from two different genes and two clones were novel sequences. Flow cytometry and immunofluorescence confirmed that CD24 protein was over-expressed in the ER-positive cell lines. We conclude that SSH and microarray technology can be successfully applied to identify differentially expressed genes. This approach allowed the identification of differentially expressed genes without the need to obtain previously cloned cDNAs.  (+info)

Identification of the genes responsive to etoposide-induced apoptosis: application of DNA chip technology. (4/28523)

DNA chip technology was used in an attempt to identify target genes responsible for apoptosis induced by etoposide, a p53 activating topoisomerase II inhibitor used clinically as an antitumor agent. 62 Individual mRNAs whose mass changed significantly were identified after screening oligonucleotide arrays capable of detecting 6591 unique human mRNA species. 12 (Nine induced and three repressed) of the etoposide-responsive genes were further studied by Northern analysis and an agreement rate of 92%, was reached. Among the 12 genes studied, two (WAF1/p21 and PCNA) are known p53 regulatory genes, two (glutathione peroxidase and S100A2 calcium-binding protein) appear to be the novel p53 target genes and the others appear to be p53-independent. Based upon these findings, the signalling pathways that possibly mediate etoposide-induced apoptosis are proposed.  (+info)

Development of an oligonucleotide-specific capture plate hybridization assay for detection of Haemophilus parasuis. (5/28523)

An oligonucleotide-specific capture plate hybridization assay has been developed to rapidly, specifically, and sensitively detect Haemophilus parasuis from nasal swabs. Several in vitro studies have been performed to determine the sensitivity and specificity of the test, and in vivo studies have validated this technique in pigs. Results suggest that the assay detects <100 colony-forming units/ml in a pure culture and gives a positive result when H. parasuis is present in a ratio of 1:10(3)-10(4) in a mixed culture, and the probe does not hybridize with other related species found in the upper respiratory tract. This assay is more sensitive than culture for detection of the microorganism from nasal swabs and lesions.  (+info)

Versatile derivatisation of solid support media for covalent bonding on DNA-microchips. (6/28523)

A chemistry was developed that permits on DNA-arrays both the covalent immobilisation of pre-fabricated nucleic acids-such as oligonucleotides, PCR-products or peptide nucleic acid oligomers-and the in situ synthesis of such compounds on either glass or polypropylene surfaces. Bonding was found to be stable even after some 30 cycles of stripping. Due to a dendrimeric structure of the linker molecule, the loading can be modified in a controlled manner and increased beyond the capacity of glass without negative effects on hybridisation efficiency. Also, the chemistry warrants the modulation of other surface properties such as charge or hydrophobicity. Preferentially, attachment of nucleic acids takes place only via the terminal amino-group of amino-modified oligonucleotides or the terminal hydroxyl-group of unmodified molecules so that the entire molecule is accessible to probe hybridisation. This derivatisation represents a support chemistry versatile enough to serve nearly all current forms of DNA-arrays or microchips.  (+info)

Timely toxicology. (7/28523)

The ToxChip, a DNA microarray chip, allows the monitoring of the expression levels of thousands of different genes at a time, thereby condensing months of painstaking laboratory tasks into a day's work. For toxicology researchers in particular, this tool is important because it promises a more effective way to identify environmental hazards and their effects on DNA. The ToxChip, developed by NIEHS scientists J. Carl Barrett, Cynthia Afshari, and Emile F. Nuwaysir, could transform the way toxicologists approach environmental problems.  (+info)

DNA microarray technology: the anticipated impact on the study of human disease. (8/28523)

One can imagine that, one day, there will be a general requirement that relevant array data be deposited, at the time of publication of manuscripts in which they are described, into a single site made available for the storage and analysis of array data (modeled after the GenBank submission requirements for DNA sequence information). With this system in place, one can anticipate a time when data from thousands of gene expression experiments will be available for meta-analysis, which has the potential to balance out artifacts from many individual studies, thus leading to more robust results and subtle conclusions. This will require that data adhere to some type of uniform structure and format that would ideally be independent of the particular expression technology used to generate it. The pros and cons of various publication modalities for these large electronic data sets have been discussed elsewhere [12], but, practical difficulties aside, general depositing must occur for this technology to reach the broadest range of investigators. Finally, as mentioned at the beginning of this review, it is unfortunate that this important research tool remains largely restricted to a few laboratories that have developed expertise in this area and to a growing number of commercial interests. Ultimately the real value of microarray technology will only be realized when this approach is generally available. It is hoped that issues including platforms, instrumentation, clone availability, and patents [20] will be resolved shortly, making this technology accessible to the broadest range of scientists at the earliest possible moment.  (+info)

RNA Transcription Detected on Chromosomes 21 and 22 Using High Density Oligonucleotide ArraysRNA Transcription Detected on Chromosomes 21 and 22 Using High Density Oligonucleotide Arrays
... Thomas R. Gingeras, Affymetrix Inc., Santa Clara, CA. The first drafts of complete human genome sequence have brought with them the opportunities to map the RNA transcription patterns that are characteristic of each differentiated and undifferentiated cell type and characterize the sequence variations that underlie the phenotypic differences observed in the human population. By using the very high information content inherent in high-density oligonucleotide arrays it will be possible to map the locations of RNA transcription along the length of the entire human genome. Such a transcriptome map will provide information concerning: 1) the identification of novel transcription domains of the genome, 2) the predominant utilization of exon sequences during differentially spliced gene expression and 3) a empirically derived set of results which can be compared to the sequence annotation now being assembled ...
EMEA Oligonucleotide DNA Microarrays (oDNA) Market 2017 Sales, Size, Shares, Trends Analysis and Growth Forecast to 2022 -...EMEA Oligonucleotide DNA Microarrays (oDNA) Market 2017 Sales, Size, Shares, Trends Analysis and Growth Forecast to 2022 -...
EMEA Oligonucleotide DNA Microarrays (oDNA) market analysis of an industry is a crucial thing for various stakeholders like investors, CEOs, traders, suppliers and others. The Oligonucleotide DNA Microarrays (oDNA) industry research report is a resource, which provides current as well as upcoming technical and financial details of the industry.. Oligonucleotide DNA Microarrays (oDNA) market 2017-2022 research report is a professional and in-depth study on the current state of this market. Various definitions and classification of the industry, applications of the industry and chain structure are given. Present day status of the Oligonucleotide DNA Microarrays (oDNA) industry policies and news are analysed.. Following are major Table of Content of Oligonucleotide DNA Microarrays (oDNA) Industry:. Oligonucleotide DNA Microarrays (oDNA) Market Competition by Manufacturers, Oligonucleotide DNA Microarrays (oDNA) Production, Revenue by Region, Oligonucleotide DNA Microarrays (oDNA) Supply, ...
DNA microarray-based identification of bacterial and fungal pathogens in bloodstream infections<...DNA microarray-based identification of bacterial and fungal pathogens in bloodstream infections<...
TY - JOUR. T1 - DNA microarray-based identification of bacterial and fungal pathogens in bloodstream infections. AU - Yoo, Seung Min. AU - Choi, JunYong. AU - Yun, Jung Kuk. AU - Choi, Jae Kyung. AU - Shin, So Youn. AU - Lee, Kyungwon. AU - Kim, June Myung. AU - Lee, Sang Yup. PY - 2010/2/1. Y1 - 2010/2/1. N2 - The accurate and rapid identification of pathogens in blood is a major challenge in clinical pathogen diagnostics because of the high mortality of sepsis. Here we report the development of DNA microarray for the identification of pathogens causing bloodstream infections. Species-specific and bacteria- and fungi-broad-ranged probes were designed to identify 50 bacteria and 7 fungi. The specificities and sensitivities of the selected probes were successfully validated by applying reference strains. To assess the performance of the DNA microarray in a clinical setting, blind tests were performed using 112 blood culture specimens that showed preliminary presence of pathogenic microorganisms ...
DNA Microarray-Based Gene Expression Profiling in Cancer: Aiding ...: Ingenta ConnectDNA Microarray-Based Gene Expression Profiling in Cancer: Aiding ...: Ingenta Connect
A DNA microarray is a solid support such as a glass slide, silicon chip or nylon membrane on which DNA molecules are attached at precise locations. Using DNA microarrays, the expression of tens of thousands of genes in a biological sample can be detected in one experiment. Emerging data suggests that the use of DNA microarrays can aid the differentiation of tumors with similar morphological appearance, predict patient outcome independently of conventional prognostic factors and select for response or resistance to specific anti-cancer therapies. DNA microarray technology thus has the potential to supplement standard diagnostic procedures in oncology and permit a more individualized approach to patient management. Prior to clinical application, however, this methodology must be simplified, standardized, evaluated in external quality assessment schemes and made available at relatively low costs. Most importantly, the preliminary, but promising, early findings must be validated by high-level ...
Can subtle changes in gene expression be consistently detected with different microarray platforms? | BMC Genomics | Full TextCan subtle changes in gene expression be consistently detected with different microarray platforms? | BMC Genomics | Full Text
The comparability of gene expression data generated with different microarray platforms is still a matter of concern. Here we address the performance and the overlap in the detection of differentially expressed genes for five different microarray platforms in a challenging biological context where differences in gene expression are few and subtle. Gene expression profiles in the hippocampus of five wild-type and five transgenic δC-doublecortin-like kinase mice were evaluated with five microarray platforms: Applied Biosystems, Affymetrix, Agilent, Illumina, LGTC home-spotted arrays. Using a fixed false discovery rate of 10% we detected surprising differences between the number of differentially expressed genes per platform. Four genes were selected by ABI, 130 by Affymetrix, 3,051 by Agilent, 54 by Illumina, and 13 by LGTC. Two genes were found significantly differentially expressed by all platforms and the four genes identified by the ABI platform were found by at least three other platforms.
Deciphering the transcriptional network of the DC lineage - ScienceOpenDeciphering the transcriptional network of the DC lineage - ScienceOpen
High density oligonucleotide array technology is widely used in many areas of biomedical research for quantitative and highly parallel measurements of gene expression. Affymetrix GeneChip arrays are the most popular. In this technology each gene is typically represented by a set of 11-20 pairs of probes. In order to obtain expression measures it is necessary to summarize the probe level data. Using two extensive spike-in studies and a dilution study, we developed a set of tools for assessing the effectiveness of expression measures. We found that the performance of the current version of the default expression measure provided by Affymetrix Microarray Suite can be significantly improved by the use of probe level summaries derived from empirically motivated statistical models. In particular, improvements in the ability to detect differentially expressed genes are demonstrated ...
A temporal precedence based clustering method for gene expression microarray data | BMC Bioinformatics | Full TextA temporal precedence based clustering method for gene expression microarray data | BMC Bioinformatics | Full Text
Time-course microarray experiments can produce useful data which can help in understanding the underlying dynamics of the system. Clustering is an important stage in microarray data analysis where the data is grouped together according to certain characteristics. The majority of clustering techniques are based on distance or visual similarity measures which may not be suitable for clustering of temporal microarray data where the sequential nature of time is important. We present a Granger causality based technique to cluster temporal microarray gene expression data, which measures the interdependence between two time-series by statistically testing if one time-series can be used for forecasting the other time-series or not. A gene-association matrix is constructed by testing temporal relationships between pairs of genes using the Granger causality test. The association matrix is further analyzed using a graph-theoretic technique to detect highly connected components representing interesting biological
A Sequence Based Validation of Gene Expression Microarray Data<...A Sequence Based Validation of Gene Expression Microarray Data<...
TY - JOUR. T1 - A Sequence Based Validation of Gene Expression Microarray Data. AU - Thallinger, Gerhard. AU - Obermayr, Eva. AU - Charoentong, Pornpimol. AU - Tong, Dan. AU - Trajanoski, Zlatko. AU - Zeillinger, Robert. PY - 2012. Y1 - 2012. UR - http://thescipub.com/ajb.toc. U2 - 10.3844/ajbsp.2012.1.9. DO - 10.3844/ajbsp.2012.1.9. M3 - Article. VL - 1. SP - 1. EP - 9. JO - American journal of bioinformatics. JF - American journal of bioinformatics. SN - 1948-9862. IS - 1. ER - ...
Preprocessing Affymetrix Microarray Data at the Probe Level - MATLAB & SimulinkPreprocessing Affymetrix Microarray Data at the Probe Level - MATLAB & Simulink
This example shows how to use MATLAB® and Bioinformatics Toolbox™ for preprocessing Affymetrix® oligonucleotide microarray probe-level data with two preprocessing techniques, Robust Multi-array Average (RMA) and GC Robust Multi-array Average (GCRMA).
62nd Annual High Blood Pressure Conference 2008: Candidate Genes for 2-Methoxyestradiol-Mediated Vasoprotective Actions in...62nd Annual High Blood Pressure Conference 2008: Candidate Genes for 2-Methoxyestradiol-Mediated Vasoprotective Actions in...
contribute to the vascular remodeling process associated with hypertension and atherosclerosis, the aims of this study were to assess the impact of 2-ME on pathophysiological pathways regulating SMC growth using transcriptional profiling. High-density oligonucleotide microarrays (Affymetrix Human Genome U_133 Plus 2.0 GeneChips) were used to identify differentially expressed genes in cultured human aortic SMCs treated with 2-ME (acutely, for 4 hrs, n=3; and chronically, for 48 hrs, n=3) and vehicle-treated time-matched controls (n=3 for each time point). Both single gene analysis (performed using Significance Analysis of Microarrays) as well as Gene Set Enrichment Analysis (GSEA, a computational method that determines whether an a priori defined set of genes shows statistically significant, concordant differences between two biological states) indicated downregulation of genes critically involved in mitotic spindle assembly and function in SMCs chronically treated with 2-ME when compared to ...
3rd Course on Introduction to Microarray Gene Expression Analysis - Ubio3rd Course on Introduction to Microarray Gene Expression Analysis - Ubio
This introductory course on microarray analysis is targeted to people without previous knowledge on this field. We will cover the basic steps that should be followed to obtain a list of differentially expressed genes, starting from raw expression data. The theoretical part of the course will be comprehensive and the similarities and differences between one- and two-color arrays will be discussed. For the practical part, an already published public dataset of Agilent two-color arrays will be used for all subsequent hands-on work. Students will get familiar with raw data format, background subtraction and normalization procedures that are needed before any differential expression analysis ...
Novel and simple transformation algorithm for combining microarray data sets | BMC Bioinformatics | Full TextNovel and simple transformation algorithm for combining microarray data sets | BMC Bioinformatics | Full Text
With microarray technology, variability in experimental environments such as RNA sources, microarray production, or the use of different platforms, can cause bias. Such systematic differences present a substantial obstacle to the analysis of microarray data, resulting in inconsistent and unreliable information. Therefore, one of the most pressing challenges in the field of microarray technology is how to integrate results from different microarray experiments or combine data sets prior to the specific analysis. Two microarray data sets based on a 17k cDNA microarray system were used, consisting of 82 normal colon mucosa and 72 colorectal cancer tissues. Each data set was prepared from either total RNA or amplified mRNA, and the difference of RNA source between these two data sets was detected by ANOVA (Analysis of variance) model. A simple integration method was introduced which was based on the distributions of gene expression ratios among different microarray data sets. The method transformed gene
Arrayit Corporation ARYC - Services - eChips - Peptide and Oligonucleotide Microarrays - Microarrays Life Sciences Diagnostics...Arrayit Corporation ARYC - Services - eChips - Peptide and Oligonucleotide Microarrays - Microarrays Life Sciences Diagnostics...
Arrayit offers complete microarray services including microarray design, microarray sample preparation, microarray labeling, microarray amplification, microarray hybridization, microarray processing, microarray scanning, and microarray data analysis. Our high-throughput microarray cleanroom facilities enable a microarray service to meet the needs of every research laboratory, biotech, pharmaceutical company, hospitical and clinic. DNA microarrays, protein microarrays, peptide microarrays and VIP microarrays are included in our services offerings.
Deciphering transcription factor binding patterns from genome-wide high density ChIP-chip tiling array data | BMC Proceedings |...Deciphering transcription factor binding patterns from genome-wide high density ChIP-chip tiling array data | BMC Proceedings |...
With the microarray technology rapidly advanced, tiling arrays have quickly become one of the most powerful tools in genome-wide investigations. High density tiling arrays [1] can be used to address many biological problems such as transcriptome mapping, protein-DNA interaction mapping (ChIP-chip) and array CGH among others [2]. ChIP-chip [3], the focus of the paper, is a technique that combines chromatin immunoprecipitation (ChIP) with microarray technology (chip). It allows efficient, scalable and comprehensive identification of binding sites and profiles of DNA-binding proteins [4]. High density ChIP-chip tiling arrays not only help us map the binding sites of a protein in the genome, but also allow us to better understand the binding events of the protein by clearly displaying the binding occupancy profiles. Several methods have been proposed to analyze the ChIP-chip data; for example, Joint Binding De-convolution (JBD) [5] uses a probabilistic graphical model to improve spatial resolution ...
CGH, CGH array, micro-macro array - Macroarray and MicroarrayCGH, CGH array, micro-macro array - Macroarray and Microarray
CGH stands for comparative genome hybridisation, which aims to compare the presence / absence / number of similar genes in 2 genomes (i.e. its a survey of genetic differences between 2 organisms). So, a CGH experiment might compare gemomic DNA from 2 closely related bacterial species or strains. The difference between CGH array experiments and gene expression array experiments is just the target which is hybridised to the array: labelled genomic DNA for CGH; labelled cDNA (or cRNA - derived from mRNA in either case) for gene expression. You can use exactly the same arrays for both types of experiment, although the objective of CGH is normally genome-wide comparison of 2 genomes, so CGH normally uses whole-genome microarrays (for prokaryotes, at least). In general, you can use any genomic array for either gene expression or CGH ...
Intra-platform comparison of 25-mer and 60-mer oligonucleotide Nimblegen DNA microarrays | BMC Research Notes | Full TextIntra-platform comparison of 25-mer and 60-mer oligonucleotide Nimblegen DNA microarrays | BMC Research Notes | Full Text
We performed a Nimblegen intra-platform microarray comparison by assessing two categories of flax target probes (short 25-mers oligonucleotides and long 60-mers oligonucleotides) in identical conditions of target production, design, labelling, hybridization, image analyses, and data filtering. We compared technical parameters of array hybridizations, precision and accuracy as well as specific gene expression profiles. Comparison of the hybridization quality, precision and accuracy of expression measurements, as well as an interpretation of differential gene expression in flax tissues were performed. Both array types yielded reproducible, accurate and comparable data that are coherent for expression measurements and identification of differentially expressed genes. 60-mers arrays gave higher hybridization efficiencies and therefore were more sensitive allowing the detection of a higher number of unigenes involved in the same biological process and/or belonging to the same multigene family. The two flax
United States DNA Microarray Market 2017- Illumnia, Affymetrix, Agilent Technologies, Roche NimbleGen - The First NewshawkUnited States DNA Microarray Market 2017- Illumnia, Affymetrix, Agilent Technologies, Roche NimbleGen - The First Newshawk
Other. The DNA Microarray report does the thorough study of the key industry players to understand their business strategies, annual revenue, company profile and their contribution to the DNA Microarray market share in the United States. Diverse factors of the DNA Microarray industry like the supply chain scenario, industry standards, import/export details are also mentioned in this report.. Key Highlights of the United States DNA Microarray Market 2017 Report:. A Clear understanding of the DNA Microarray market based on growth, constraints, opportunities, feasibility study.. Concise DNA Microarray Market study based on major United States regions.. Analysis of evolving market segments as well as a complete study of existing DNA Microarray market segments.. Before Purchasing, Request Free Sample Copy of the Report Here: http://qyresearch.us/report/united-states-dna-microarray-market-2017/107122/#requestForSample. Furthermore, distinct aspects of DNA Microarray market like the technological ...
Identifying genes relevant to specific biological conditions in time course microarray experimentsIdentifying genes relevant to specific biological conditions in time course microarray experiments
Microarrays have been useful in understanding various biological processes by allowing the simultaneous study of the expression of thousands of genes. However, the analysis of microarray data is a challenging task. One of the key problems in microarray analysis is the classification of unknown expression profiles. Specifically, the often large number of non-informative genes on the microarray adversely affects the performance and efficiency of classification algorithms. Furthermore, the skewed ratio of sample to variable poses a risk of overfitting. Thus, in this context, feature selection methods become crucial to select relevant genes and, hence, improve classification accuracy. In this study, we investigated feature selection methods based on gene expression profiles and protein interactions. We found that in our setup, the addition of protein interaction information did not contribute to any significant improvement of the classification results. Furthermore, we developed a novel feature ...
Correction of unexpected distributions of P values from analysis of whole genome arrays by rectifying violation of statistical...Correction of unexpected distributions of P values from analysis of whole genome arrays by rectifying violation of statistical...
A literature search for non-uniform distributions of P values shows few citations [3, 5] and these both relate to statistical tests applied to expression results generated using Affymetrix microarrays. Huang et al. [5] compare gene expression profiles of tumours in three groups of mice using an Affymetrix Mouse Genechip array. When an ANOVA was performed on the expression of around 23,000 genes, a distribution of P values similar to Figure 1 was obtained. However when a t-test was applied to 2 of these groups, a distribution of P values similar to Figure 3 was obtained. The authors hypothesised that the reason for such a non-uniform distribution was due to excess biological similarity between some samples in the groups used for the t-test. This excess biological similarity was thought to be due to 2 pairs of samples being littermates of the same age and a further 2 pairs of samples were assayed at the same time. This resulted in the samples used for the t-test not being statistically ...
Profound effect of normalization on detection of differentially expressed genes in oligonucleotide microarray data analysis |...Profound effect of normalization on detection of differentially expressed genes in oligonucleotide microarray data analysis |...
Oligonucleotide microarrays measure the relative transcript abundance of thousands of mRNAs in parallel. A large number of procedures for normalization and detection of differentially expressed genes have been proposed. However, the relative impact of these methods on the detection of differentially expressed genes remains to be determined. We have employed four different normalization methods and all possible combinations with three different statistical algorithms for detection of differentially expressed genes on a prototype dataset. The number of genes detected as differentially expressed differs by a factor of about three. Analysis of lists of genes detected as differentially expressed, and rank correlation coefficients for probability of differential expression shows that a high concordance between different methods can only be achieved by using the same normalization procedure. Normalization has a profound influence of detection of differentially expressed genes. This influence is higher than
Gene chip analysis - WikipediaGene chip analysis - Wikipedia
Microarray technology is a powerful tool for genomic analysis. It gives a global view of the genome in a single experiment. Data analysis of the microarray is a vital part of the experiment. Each microarray study comprises multiple microarrays, each giving tens of thousands of data points. Since the volume of data is growing exponentially as microarrays grow larger, the analysis becomes more challenging. In general the greater the volume of data, the more chances arise for erroneous results. Handling such large volumes of data requires high-end computational infrastructures and programs that can handle multiple data formats. There are already programs available for microarray data analysis on various platforms. However, due to rapid development, diversity in microarray technology, and different data formats, there is always the need for more comprehensive and complete microarray data analysis. Proper data processing and quality control are critical to the validity and interpretability of gene ...
Microarray analysis provides new insights into the function of apolipoprotein O in HepG2 cell line | Lipids in Health and...Microarray analysis provides new insights into the function of apolipoprotein O in HepG2 cell line | Lipids in Health and...
Apolipoprotein O (apoO) is a new member of the apolipoprotein family. However, data on its physiological functions are limited and inconsistent. Using a microarray expression analysis, this study explored the function of apoO in liver cells. HepG2 cells were treated either with oleic acid or tumor necrosis factor-α for 24 h. mRNA and protein expression of apoO were assessed by quantitative real-time PCR (qRT-PCR) and Western blot respectively. An efficient lentiviral siRNA vector targeting the human apoO gene was designed and constructed. The gene expression profile of HepG2 human hepatocellular carcinoma cells transfected with the apoO silencing vector was investigated using a whole-genome oligonucleotide microarray. The expression levels of some altered genes were validated using qRT-PCR. ApoO expression in HepG2 cells was dramatically affected by lipid and inflammatory stimuli. A total of 282 differentially expressed genes in apoO-silenced HepG2 cells were identified by microarray analysis. These
We have assessed the tool of RNA titration examples for evaluatingWe have assessed the tool of RNA titration examples for evaluating
immune Uncategorized 155294-62-5 IC50, Rabbit Polyclonal to SNX4. We have assessed the tool of RNA titration examples for evaluating microarray system functionality and the influence of different normalization methods over the outcomes obtained. widespread make use of, many locally are concerned using the comparability from the outcomes attained using different microarray systems and therefore the natural relevance from the qualitative and quantitative outcomes obtained. Microarray system functionality has been examined before over the requirements of awareness, specificity, powerful range, accuracy1C12 and precision. Within the MicroArray Quality Control (MAQC) task, very similar assessments have already been reported13 also,14. Other research have used described mixtures of RNA examples (titration examples) for interplatform2,15 and interlaboratory15 evaluations. Here weve investigated an alternative solution functionality metric: the talents of different microarray systems to accurately ...
Dr Marta Milo - Marta Milo - Research - Biomedical Science - The University of SheffieldDr Marta Milo - Marta Milo - Research - Biomedical Science - The University of Sheffield
Microarrays provided a practical method for measuring the expression of thousand of genes simultaneously. Although next generation sequencing has mainly replaced these assays, there is still a large amount of data available in public databases, that would enable to better design sequencing experiment with the insight of an high-throughput gene expression screening. For this reasons methods that have been developed in the past to analyse microarrays gene expression data, are still a valuable resource. Microarray technology is associated with many significant sources of experimental uncertainty, which must be considered in order to make confident inference from the data. Estimate of uncertainty is not entirely achieved using repeat experiments. Outliers are often due to flaws in the microarray technique or to problems in the hybridization of the biological material. In high-density oligonucleotide arrays as well as in cDNA spotted arrays the aim is to extract from pixel intensity signals an ...
Expression monitoring by hybridization to high-density oligonucleotide arraysExpression monitoring by hybridization to high-density oligonucleotide arrays
The human genome encodes approximately 100,000 different genes, and at least partial sequence information for nearly all will be available soon. Sequence information alone, however, is insufficient for a full understanding of gene function, expression, regulation, and splice-site variation. Because …
Microarray Detection and Characterization of Bacterial Foodborne Pathogens, Buch - ReadRateMicroarray Detection and Characterization of Bacterial Foodborne Pathogens, Buch - ReadRate
Microarray Detection and Characterization of Bacterial Foodborne Pathogens und Buchbewertungen gibt es auf ReadRate.com. Bücher können hier direkt online erworben werden.
January | 2015 | PhosphatasesJanuary | 2015 | Phosphatases
STAT6 up or down regulation was defined like a 2 fold big difference in the imply expression degree within a offered information set. For examination ple, up regulation between GBM patients refers to a two fold increase in STAT6 expression, com pared to your normal STAT6 expression levels in all individuals inside of the GBM sub population. Therefore, just about every patient Inhibitors,Modulators,Libraries sub population has a distinct baseline, and person individuals STAT6 expression levels are only compared to other sufferers in the same sub population. Affymetrix microarray Microarray analysis of Affymetrix chips was performed as previously described in. Briefly, complete RNA was extracted from wild style and STAT6 deficient U 1242MG and U 87MG cells. Biotin labeled cRNA was ready from somewhere around two ug of total RNA and hybridized to Human Genome U133 plus two Affymetrix oligonucleotide arrays, which incorporate roughly 56,400 transcripts of human genes or ESTs.. Soon after washing ...
Normalization of Illumina Infinium whole-genome SNP data improves copy number estimates and allelic intensity ratios. | MAD for...Normalization of Illumina Infinium whole-genome SNP data improves copy number estimates and allelic intensity ratios. | MAD for...
BACKGROUND: Illumina Infinium whole genome genotyping (WGG) arrays are increasingly being applied in cancer genomics to study gene copy number alterations and allele-specific aberrations such as loss-of-heterozygosity (LOH). Methods developed for normalization of WGG arrays have mostly focused on diploid, normal samples. However, for cancer samples genomic aberrations may confound normalization and data interpretation. Therefore, we examined the effects of the conventionally used normalization method for Illumina Infinium arrays when applied to cancer samples. RESULTS: We demonstrate an asymmetry in the detection of the two alleles for each SNP, which deleteriously influences both allelic proportions and copy number estimates. The asymmetry is caused by a remaining bias between the two dyes used in the Infinium II assay after using the normalization method in Illuminas proprietary software (BeadStudio). We propose a quantile normalization strategy for correction of this dye bias. We tested the ...
Identification of cell surface marker candidates on SV-T2 cells using DNA microarray on DLC-coated glass<...Identification of cell surface marker candidates on SV-T2 cells using DNA microarray on DLC-coated glass<...
TY - JOUR. T1 - Identification of cell surface marker candidates on SV-T2 cells using DNA microarray on DLC-coated glass. AU - Tuoya, AU - Hirayama, Koichi. AU - Nagaoka, Tadahiro. AU - Yu, Dongwei. AU - Fukuda, Takayuki. AU - Tada, Hiroko. AU - Yamada, Hidenori. AU - Seno, Masaharu. PY - 2005/8/19. Y1 - 2005/8/19. N2 - We analyzed gene expression profiles of normal mouse fibroblast BALB/c 3T3 cells and its SV40 transformant SV-T2 cells using our originally developed cell surface marker DNA microarray, which is prepared on a diamond-like carbon-coated glass. As a result, CD62L and IL-6 receptor α gene expressions were upregulated in SV-T2 and were thought to be candidates for cell surface markers of the cells. The result of microarray analysis was validated by real-time quantitative PCR, immunohistochemistry and biological assays. These data show that our cell surface marker DNA microarray should be useful in finding the candidates of cell type-specific surface markers.. AB - We analyzed gene ...
Metastasis-associated Differences in Gene Expression in a Murine Model of Osteosarcoma | Cancer ResearchMetastasis-associated Differences in Gene Expression in a Murine Model of Osteosarcoma | Cancer Research
The well-defined differences in metastatic behavior and the clonal relationship of the K7M2 and K12 cells allowed the use of cDNA microarrays to define potentially important genetic determinants for pulmonary metastasis in this model. Recently, cDNA microarray technology has been used to list genes that are differentially expressed between high and low metastatic tumor systems (18, 19, 20) . Data generated in such cDNA microarray comparisons are of considerable value; however, it is difficult to determine how best to use this information. Both traditional reductionist and novel bio-informatic approaches (including hierarchical cluster analyses) have been used to manage microarray data. In the cDNA microarray comparisons presented herein, we identified 53 genes that were differentially expressed between the high (K7M2) and the low (K12) metastatic OSA primary tumors. To use this information, we used a reductionist approach that was based on biological differences demonstrated between the high and ...
Genetic Modifiers: polymorphism markers in ArabidopsisGenetic Modifiers: polymorphism markers in Arabidopsis
and Shahdara. Gene expression markers (GEMs) are based on differences in transcript levels that exhibit bimodal distributions in segregating progeny, while single feature polymorphism (SFP) markers rely on differences in hybridization to individual oligonucleotide probes. Unlike SFPs, GEMs can be derived from any type of DNA-based expression microarray. Our method identifies SFPs independent of a genes expression level. Alleles for each GEM and SFP marker were ascertained with GeneChip data from parental accessions as well as RILs; a novel algorithm for allele determination using RIL distributions capitalized on the high level of genetic replication per locus. GEMs and SFP markers provided robust markers in 187 and 968 genes, respectively, which allowed estimation of gene order consistent with that predicted from the Col-0 genomic sequence. Using microarrays on a population to simultaneously measure gene expression variation and obtain genotypic data for a linkage map will facilitate expression ...
Identifying differentially expressed genes in time-course microarray experiment without replicate | ScholarBank@NUSIdentifying differentially expressed genes in time-course microarray experiment without replicate | [email protected]
Replication of time series in microarray experiments is costly. To analyze time series data with no replicate, many model-specific approaches have been proposed. However, they fail to identify the genes whose expression patterns do not fit the pre-defined models. Besides, modeling the temporal expression patterns is difficult when the dynamics of gene expression in the experiment is poorly understood. We propose a method called Partial Energy ratio for Microarray (PEM) for the analysis of time course microarray data. In the PEM method, we assume the gene expressions vary smoothly in the temporal domain. This assumption is comparatively weak and hence the method is general enough to identify genes expressed in unexpected patterns. To identify the differentially expressed genes, a new statistic is developed by comparing the energies of two convoluted profiles. We further improve the statistic for microarray analysis by introducing the concept of partial energy. The PEM statistic can be easily ...
The influence of RNA integrity, purity and cDNA labelling on glass slide cDNA microarray image quality | Genome Biology | Full...The influence of RNA integrity, purity and cDNA labelling on glass slide cDNA microarray image quality | Genome Biology | Full...
The accuracy of gene expression measurements generated using cDNA microarrays is dependent on the quality of the image generated following hybridization of fluorescently labelled cDNA. It is not known how this image is influenced by sample preparation factors which such as RNA quality, cDNA synthesis and labelling efficiency. In this study we used a simple metric based on the ratio of the total feature (F) and background (B) fluorescence, which correlates with the visual assessment of 60 microarray images, to determine the influence of sample preparation on image quality. Results indicate that RNA purity (A260/A280) and integrity (18S:28S ratio) do not strongly influence microarray image quality. cDNA having an nucleotide to dye ratio greater than 100 produced poor microarray images, however, cDNA labelled more efficiently was not a guarantee of a better image. The data also indicate that the array image quality is not improved by loading more cDNA into the hybridization mixture however poor image
Genome-scale ChIP-chip analysis using 10,000 human cells. - Science ExchangeGenome-scale ChIP-chip analysis using 10,000 human cells. - Science Exchange
The technique of chromatin immunoprecipitation (ChIP) is a powerful method for identifying in vivo DNA binding sites of transcription factors and for studying chromatin modifications. Unfortunately, the large number of cells needed for the standard ChIP protocol has hindered the analysis of many biologically interesting cell populations that are difficult to obtain in large numbers. New ChIP methods involving the use of carrier chromatin have been developed that allow the one-gene-at-a-time analysis of very small numbers of cells. However such methods are not useful if the resultant sample will be applied to genomic microarrays or used in ChIP-sequencing assays. Therefore, we have miniaturized the ChIP protocol such that as few as 10,000 cells (without the addition of carrier reagents) can be used to obtain enough sample material to analyze the entire human genome. We demonstrate the reproducibility of this MicroChIP technique using 2.1 million feature high-density oligonucleotide arrays and ...
Preprocessing Affymetrix® Microarray Data at the Probe LevelPreprocessing Affymetrix® Microarray Data at the Probe Level
Adjusting background for chip # 1 of 42 using MLE method. Adjusting background for chip # 2 of 42 using MLE method. Adjusting background for chip # 3 of 42 using MLE method. Adjusting background for chip # 4 of 42 using MLE method. Adjusting background for chip # 5 of 42 using MLE method. Adjusting background for chip # 6 of 42 using MLE method. Adjusting background for chip # 7 of 42 using MLE method. Adjusting background for chip # 8 of 42 using MLE method. Adjusting background for chip # 9 of 42 using MLE method. Adjusting background for chip # 10 of 42 using MLE method. Adjusting background for chip # 11 of 42 using MLE method. Adjusting background for chip # 12 of 42 using MLE method. Adjusting background for chip # 13 of 42 using MLE method. Adjusting background for chip # 14 of 42 using MLE method. Adjusting background for chip # 15 of 42 using MLE method. Adjusting background for chip # 16 of 42 using MLE method. Adjusting background for chip # 17 of 42 using MLE method. Adjusting ...
Arrays of arrays promise more efficient gene expression profilesArrays of arrays promise more efficient gene expression profiles
Researchers use DNA microarrays, or gene chips, to distinguish among different types of tissues based on the expression patterns of thousands of genes. A new study says the technology can be modified to profile more tissue samples simultaneously and with greater efficiency. The innovation is called an array of arrays. Gene expression profiles are typically obtained one at a time by hybridizing a single tissue sample to a single array on an individual glass slide. The integrated device described in the study is a glass wafer that includes 49 individual oligonucleotide arrays arranged as a 7 × 7 array of arrays. David J. Lockhart and colleagues at the Genomics Institute of the Novartis Research Foundation, in San Diego, California, developed a way to hybridize many tissue samples to multiple arrays on a single glass slide, or wafer. Using this and other modifications, they completed a study of gene expression in ovarian cancer in a single experiment. This was done in a fraction of the time and ...
The balance of reproducibility, sensitivity, and specificity of lists of differentially expressed genes in microarray studiesThe balance of reproducibility, sensitivity, and specificity of lists of differentially expressed genes in microarray studies
Background Reproducibility is a fundamental requirement in scientific experiments. Some recent publications have claimed that microarrays are unreliable because lists of differentially expressed genes (DEGs) are not reproducible in similar experiments. Meanwhile, new statistical methods for identifying DEGs continue to appear in the scientific literature. The resultant variety of existing and emerging methods exacerbates confusion and continuing debate in the microarray community on the appropriate choice of methods for identifying reliable DEG lists. Results Using the data sets generated by the MicroArray Quality Control (MAQC) project, we investigated the impact on the reproducibility of DEG lists of a few widely used gene selection procedures. We present comprehensive results from inter-site comparisons using the same microarray platform, cross-platform comparisons using multiple microarray platforms, and comparisons between microarray results and those from TaqMan - the widely regarded ...
At-TAX: a whole genome tiling array resource for developmental expression analysis and transcript identification in Arabidopsis...At-TAX: a whole genome tiling array resource for developmental expression analysis and transcript identification in Arabidopsis...
Gene expression maps for model organisms, including Arabidopsis thaliana, have typically been created using gene-centric expression arrays. Here, we describe a comprehensive expression atlas, Arabidopsis thaliana Tiling Array Express (At-TAX), which is based on whole-genome tiling arrays. We demonst …
Plus itPlus it
1567 With microarray data we successfully developed a novel system for predicting early intrahepatic recurrence of hepatocellular carcinoma (HCC) [1]. The HCC microarray data consists of 60 HCC patients with high-density oligonucleotide microarrays representing approximately 6000 genes. In this data, the 20 patients had early intrahepatic recurrence within 1 year after curative surgery and 40 patients had nonrecurrence. We randomly divided 60 samples into 33 training samples and 27 blinded samples. With 33 training samples, we selected 12 genes useful for prediction. In general, visualization of high-dimensional space is important to evaluate interactively genes and to elucidate mechanism of recurrence. The Karhunen-Loeve (KL) expansion [2], which corresponds to PCA, and the Sammons nonlinear mapping (SNM) [3], which corresponds to MDS, are popular visualization methods. We call these methods unsupervised visualization where labeled samples are not used. In this paper we propose visualization ...
Microarray-based identification of Pitx3 targets during Xenopus embryo by L Hooker, C Smoczer et al."Microarray-based identification of Pitx3 targets during Xenopus embryo" by L Hooker, C Smoczer et al.
Background: Unexpected phenotypes resulting from morpholino-mediated translational knockdown of Pitx3 in Xenopus laevis required further investigation regarding the genetic networks in which the gene might play a role. Microarray analysis was, therefore, used to assess global transcriptional changes downstream of Pitx3. Results: From the large data set generated, selected candidate genes were confirmed by reverse transcriptase-polymerase chain reaction (RT-PCR) and in situ hybridization. Conclusions: We have identified four genes as likely direct targets of Pitx3 action: Pax6, beta Crystallin-b1 (Crybb1), Hes7.1, and Hes4. Four others show equivocal promise worthy of consideration: Vent2, and Ripply2 (aka Ledgerline or Stripy), eFGF and RXRa. We also describe the expression pattern of additional and novel genes that are Pitx3-sensitive but that are unlikely to be direct targets.
Solving the riddle of the bright mismatches: labeling and effective binding in oligonucleotide arraysSolving the riddle of the bright mismatches: labeling and effective binding in oligonucleotide arrays
RNA binding to high-density oligonucleotide arrays has shown tantalizing differences with solution experiments. We analyze here its sequence specificity, fitting binding affinities to sequence composition in large datasets. Our results suggest that the fluorescent labels interfere with binding, causing a catch-22. To be detected, the RNA must both glow and bind: without labels it cannot be seen even if bound, while with too many it will not bind. A simple model for the binding of labeled oligonucleotides sheds light on the interplay between binding energies and labeling probability.. Note: Comment in: Phys Rev E Stat Nonlin Soft Matter Phys. 2006 Jun;73(6 Pt 1):063901; author reply 063902. ...
Affymetrix Microarrays Platform (PAM) | BioCoresAffymetrix Microarrays Platform (PAM) | BioCores
Affymetrix® Microarrays Platform (PAM) is a service focused on DNA and RNA microarray solutions offered by Affymetrix, with the main goal to offer solutions towards a personalized medicine. We offer microarrays for expression and for cytogenetics studies, from the basic research to applied research and diagnosis.PAM is an Affymetrix European Reference Group for Cytogenetic
Identification of genes differentially regulated by interferon α, β, or γ using oligonucleotide arrays | PNASIdentification of genes differentially regulated by interferon α, β, or γ using oligonucleotide arrays | PNAS
We have used oligonucleotide arrays to study the changes in mRNA expression after stimulation of the human HT1080 cell line with different IFNs. The effectiveness of this approach was evident by the ability to successfully identify and quantify the mRNA levels for many known ISGs. Previous Northern blot analyses of HT1080 cells showed that while IFN-α induced 6-16 mRNA levels by more than 20-fold, there was no detectable induction by IFN-γ; also, 9-27 mRNA levels were induced by both IFN-α and IFN-γ, although the level of 9-27 induction by IFN-α was 3-fold higher than by IFN-γ (5). These characteristics were replicated with remarkable similarity by the oligonucleotide arrays: 6-16 was absent in untreated cells and induced at least 20- and 21-fold by IFN-α or IFN-β, respectively, but not by IFN-γ; 9-27 was induced 23- and 22-fold by IFN-α or IFN-β and 8-fold by IFN-γ (Fig. 1 and Table 2). The consistency between our data and previous studies regarding IFN-specific inducibility further ...
Oligonucleotide Array Sequence Analysis (Topic) - Rensselaer LibrariesOligonucleotide Array Sequence Analysis (Topic) - Rensselaer Libraries
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Microarray gene expression profiling of osteoarthritic bone suggests altered bone remodelling, WNT and transforming growth...Microarray gene expression profiling of osteoarthritic bone suggests altered bone remodelling, WNT and transforming growth...
Osteoarthritis (OA) is characterized by alterations to subchondral bone as well as articular cartilage. Changes to bone in OA have also been identified at sites distal to the affected joint, which include increased bone volume fraction and reduced bone mineralization. Altered bone remodelling has been proposed to underlie these bone changes in OA. To investigate the molecular basis for these changes, we performed microarray gene expression profiling of bone obtained at autopsy from individuals with no evidence of joint disease (control) and from individuals undergoing joint replacement surgery for either degenerative hip OA, or fractured neck of femur (osteoporosis [OP]). The OP sample set was included because an inverse association, with respect to bone density, has been observed between OA and the low bone density disease OP. Compugen human 19K-oligo microarray slides were used to compare the gene expression profiles of OA, control and OP bone samples. Four sets of samples were analyzed, comprising 10
DNA Microarray Gene Expression Analysis of a Vocal Fold Polyp and Granuloma | Journal of Speech, Language, and Hearing Research...DNA Microarray Gene Expression Analysis of a Vocal Fold Polyp and Granuloma | Journal of Speech, Language, and Hearing Research...
Genome-wide transcriptional profiling has important applications in advancing knowledge of vocal fold biology. With the use of DNA microarray technology, analysis of global patterns of gene expression can reveal unexpected networks of coordinated regulation in the extracellular matrix of the lamina propria. Transcriptional gene expression patterns for 2 vocal fold pathologies-vocal fold polyp (VP; N= 1) and vocal fold granuloma (VG; N= 1) were analyzed by means of DNA microarray analysis for 4,632 human genes using another patients true vocal fold (TVF; N= 1) as a control. Twenty-four and 29 genes for VG and VP, respectively, were established to be either over- or underexpressed compared to that of TVF. Five-way cluster analysis revealed broad patterns that suggest a potential degree of organization underlying gene expression in these tissues. For the 1 VG, genes involved represent inflammation and wound healing; for the 1 VP, involved genes demonstrate a tempered wound repair response and ...
Incorporating prior biological knowledge for network-based differential gene expression analysis using differentially weighted...Incorporating prior biological knowledge for network-based differential gene expression analysis using differentially weighted...
Abstract Background Conventional differential gene expression analysis by methods such as students t-test, SAM, and Empirical Bayes often searches for statistically significant genes without considering the interactions among them. Network-based approaches provide a natural way to study these interactions and to investigate the rewiring interactions in disease versus control groups. In this paper, we apply weighted graphical LASSO (wgLASSO) algorithm to integrate a data-driven network model with prior biological knowledge (i.e., protein-protein interactions) for biological network inference. We propose a novel differentially weighted graphical LASSO (dwgLASSO) algorithm that builds group-specific networks and perform network-based differential gene expression analysis to select biomarker candidates by considering their topological differences between the groups. Results Through simulation, we showed that wgLASSO can achieve better performance in building biologically relevant networks than ...
Application of affymetrix array and massively parallel signature sequencing for identification of genes involved in prostate...Application of affymetrix array and massively parallel signature sequencing for identification of genes involved in prostate...
Background: Affymetrix GeneChip Array and Massively Parallel Signature Sequencing (MPSS) are two high throughput methodologies used to profile transcriptomes. Each method has certain strengths and weaknesses; however, no comparison has been made between the data derived from Affymetrix arrays and MPSS. In this study, two lineage-related prostate cancer cell lines, LNCaP and C4-2, were used for transcriptome analysis with the aim of identifying genes associated with prostate cancer progression. Methods: Affymetrix GeneChip array and MPSS analyses were performed. Data was analyzed with GeneSpring 6.2 and in-house perl scripts. Expression array results were verified with RT-PCR. Results: Comparison of the data revealed that both technologies detected genes the other did not. In LNCaP, 3,180 genes were only detected by Affymetrix and 1,169 genes were only detected by MPSS. Similarly, in C4-2, 4,121 genes were only detected by Affymetrix and 1,014 genes were only detected by MPSS. Analysis of the ...
Evaluation of TransPlex Whole Transcriptome Amplification method for microarray gene expression profiling | Archivio...Evaluation of TransPlex Whole Transcriptome Amplification method for microarray gene expression profiling | Archivio...
The increased use of microarray expression profiling to study both the molecular biology of cancer and the cellular physiology of difficult-to-isolate cell types has led to a growing need for methods that allow the use of limiting quantities of RNA. This limitation has prompted the development of amplification methods that produce the quantities of RNA required for microarray analysis. Efforts have become increasingly focused upon developing a protocol that minimizes amplification bias, provides versatility, and reduces technical complexity. We evaluated the new protocol Transplex™ Whole Transcriptome Amplification (WTA) produced by Rubicon Genomics. The kit was tested on Human Reference RNA (Stratagene) and on RNA extracted from a renal tumor cell line. Reproducibility, sensitivity and reliability in calling differentially expressed genes were evaluated by both Real-Time PCR and GeneChip® technology (Affymetrix). We tested reproducibility by comparing the expression profiles provided by U133 ...
Routine use of microarray-based gene expression profiling to identify patients with low cytogenetic risk acute myeloid leukemia...Routine use of microarray-based gene expression profiling to identify patients with low cytogenetic risk acute myeloid leukemia...
Gene expression profiling has shown its ability to identify with high accuracy low cytogenetic risk acute myeloid leukemia such as acute promyelocytic leukemia and leukemias with t(8;21) or inv(16). The aim of this gene expression profiling study was to evaluate to what extent suboptimal samples with low leukemic blast load (range, 2-59%) and/or poor quality control criteria could also be correctly identified. Specific signatures were first defined so that all 71 acute promyelocytic leukemia, leukemia with t(8;21) or inv(16)-AML as well as cytogenetically normal acute myeloid leukemia samples with at least 60% blasts and good quality control criteria were correctly classified (training set). The classifiers were then evaluated for their ability to assign to the expected class 111 samples considered as suboptimal because of a low leukemic blast load (n = 101) and/or poor quality control criteria (n = 10) (test set). With 10-marker classifiers, all training set samples as well as 97 of the 101 test
Overlay analysis of the oligonucleotide array gene expression profiles and copy number abnormalities as determined by array...Overlay analysis of the oligonucleotide array gene expression profiles and copy number abnormalities as determined by array...
TY - JOUR. T1 - Overlay analysis of the oligonucleotide array gene expression profiles and copy number abnormalities as determined by array comparative genomic hybridization in medulloblastomas. AU - Lo, Ken C.. AU - Rossi, Michael R.. AU - Burkhardt, Tania. AU - Pomeroy, Scott L.. AU - Cowell, John K.. PY - 2007/1/1. Y1 - 2007/1/1. N2 - Combined analysis of gene expression array data and array-based comparative genomic hybridization data have been used in a series of 26 pediatric brain tumors to define up- and downregulated genes that coincide with losses, gains, and amplifications involving specific chromosome regions. Frequent losses were defined in chromosome arms 3q, 6q, 8p, 10q, 16q, 17p, and gains were identified in chromosome 7, and chromosome arms 9p and 17q. Amplification of a 2p region was seen in only one tumor, which corresponded to increased expression of the MYCN and DDX1 genes. To facilitate the analysis of the two data sets, we have developed a custom overlay tool that defines ...
Global gene expression analysis reveals pathway differences between teratogenic and non-teratogenic exposure concentrations of...Global gene expression analysis reveals pathway differences between teratogenic and non-teratogenic exposure concentrations of...
Global gene expression analysis reveals pathway differences between teratogenic and non-teratogenic exposure concentrations of bisphenol A and 17β-estradiol in embryonic zebrafish.
Self-organizing latent lattice models for temporal gene expression profiling<...Self-organizing latent lattice models for temporal gene expression profiling<...
TY - JOUR. T1 - Self-organizing latent lattice models for temporal gene expression profiling. AU - Zhang, Byoung Tak. AU - Yang, Jinsan. AU - Chi, Sung Wook. N1 - Funding Information: This work was supported by the Korean Government through BK21-IT, BrainTech, IMT2000 Bioinformatics and NRL Programs.. PY - 2003/7. Y1 - 2003/7. N2 - DNA microarrays are a high-throughput technology useful for functional genomics and gene expression analysis. While many microarray data are generated in sequence, most expression analysis tools are not utilizing the temporal information. Temporal expression profiling is important in many applications, including developmental studies, pathway analysis, and disease prognosis. In this paper, we develop a learning method designed for temporal gene expression profiling from massive DNA-microarray data. It attempts to learn probabilistic lattice maps of the gene expressions, which are then used for profiling the trajectories of temporal expressions of co-regulated genes. ...
TimeXNet: Identifying active gene sub-networks using time-course gene expression profiles | BMC Systems Biology | Full TextTimeXNet: Identifying active gene sub-networks using time-course gene expression profiles | BMC Systems Biology | Full Text
Time-course gene expression profiles are frequently used to provide insight into the changes in cellular state over time and to infer the molecular pathways involved. When combined with large-scale molecular interaction networks, such data can provide information about the dynamics of cellular response to stimulus. However, few tools are currently available to predict a single active gene sub-network from time-course gene expression profiles. We introduce a tool, TimeXNet, which identifies active gene sub-networks with temporal paths using time-course gene expression profiles in the context of a weighted gene regulatory and protein-protein interaction network. TimeXNet uses a specialized form of the network flow optimization approach to identify the most probable paths connecting the genes with significant changes in expression at consecutive time intervals. TimeXNet has been extensively evaluated for its ability to predict novel regulators and their associated pathways within active gene sub-networks
Comparative study of joint analysis of microarray gene expression data in survival prediction and risk assessment of breast...Comparative study of joint analysis of microarray gene expression data in survival prediction and risk assessment of breast...
Microarray gene expression data sets are jointly analyzed to increase statistical power. They could either be merged together or analyzed by meta-analysis. For a given ensemble of data sets, it cannot be foreseen which of these paradigms, merging or meta-analysis, works better. In this article, three joint analysis methods, Z-score normalization, ComBat and the inverse normal method (meta-analysis) were selected for survival prognosis and risk assessment of breast cancer patients. The methods were applied to eight microarray gene expression data sets, totaling 1324 patients with two clinical endpoints, overall survival and relapse-free survival. The performance derived from the joint analysis methods was evaluated using Cox regression for survival analysis and independent validation used as bias estimation. Overall, Z-score normalization had a better performance than ComBat and meta-analysis. Higher Area Under the Receiver Operating Characteristic curve and hazard ratio were also obtained when ...
Microarray Analysis of Differential Gene Expression Profile in Peripheral Blood Cells of Patients with Human Essential...Microarray Analysis of Differential Gene Expression Profile in Peripheral Blood Cells of Patients with Human Essential...
1. Chockalingm A, Campbell NR, Fodor JG. Worldwide epidemic of hypertension. Can J Cardio. 2006;22:553-555 2. Tomson J, Lip GYH. Blood Pressure demographic: nature or nurture…… genes or environment?. BMC Med. 2005;3:3 3. WHO. World Health Report 2002: Reducing Risks, Promoting Healthy life. Geneva: World Health Organization. 2002 4. Heller RA. et al. Discovery and analysis of inflammatory disease related genes using cDNA microarrays. Proc Nat Acad Sci. 1997;94:2150- 2155 5. Lockhart DJ, Dong H, Byrne MC, Follettie MT, Gallo MV, Chee MS, Mittmann M, Wang C, Kobayashi M, Horton H, Brown EL. Expression monitoring by hybridization to high-density oligonucleotide arrays. Nat Biotechnol. 1996;14:1675-80 6. Tzouvelekis A, Patlakas G, Bouros D. Application of Microarray Technology in pulmonary diseases. Respir Res. 2004;5:26 7. King HC, Sinha AA. Gene expression profile analysis by DNA microarrays: promise and pitfalls. JAMA. 2001;286:2280-2288 8. LI JJ. Inflammation in hypertension: primary ...
Global Gene Expression Profiling in Retinopathy of Prematurity | IOVS | ARVO JournalsGlobal Gene Expression Profiling in Retinopathy of Prematurity | IOVS | ARVO Journals
Purpose: Retinopathy of prematurity (ROP) is a common blinding disease caused by the abnormal growth of blood vessels in the retina of premature babies with low birth weight and low gestation period. However, the mechanisms and factors contributing to the progression of ROP are still unknown. The present study aimed to identify gene(s) responsible for ROP progression by a global gene expression profiling.. Methods: From a cohort of 600 subjects comprising ROP babies (n=350) and controls (n=250), 15 ROP babies at any stage (gestational age [GA] ≤ 35 weeks and/or birth weight [BW] ≤ 1700 g) and premature babies with no ROP (n=6) (GA ≤ 35 weeks and/or BW ≤ 1700 g) and full term babies of the same age and no ROP (n=3), were screened. RNA was isolated from 0.5-1 ml of blood using RNeasy mini kit from Qiagen and the purity and integrity of RNA was checked with Bioanalyzer 2100 (Agilent). Global gene expression profiling was performed by using Illumina bead Chip array having ~47,000 ...
Sensors | Free Full-Text | Kernel Based Nonlinear Dimensionality Reduction and Classification for Genomic Microarray | NotesSensors | Free Full-Text | Kernel Based Nonlinear Dimensionality Reduction and Classification for Genomic Microarray | Notes
Genomic microarrays are powerful research tools in bioinformatics and modern medicinal research because they enable massively-parallel assays and simultaneous monitoring of thousands of gene expression of biological samples. However, a simple microarray experiment often leads to very high-dimensional data and a huge amount of information, the vast amount of data challenges researchers into extracting the important features and reducing the high dimensionality. In this paper, a nonlinear dimensionality reduction kernel method based locally linear embedding(LLE) is proposed, and fuzzy K-nearest neighbors algorithm which denoises datasets will be introduced as a replacement to the classical LLEs KNN algorithm. In addition, kernel method based support vector machine (SVM) will be used to classify genomic microarray data sets in this paper. We demonstrate the application of the techniques to two published DNA microarray data sets. The experimental results confirm the superiority and high success rates of
A Brassica Exon Array for Whole-Transcript Gene Expression ProfilingA Brassica Exon Array for Whole-Transcript Gene Expression Profiling
Affymetrix GeneChip® arrays are used widely to study transcriptional changes in response to developmental and environmental stimuli. GeneChip® arrays comprise multiple 25-mer oligonucleotide probes per gene and retain certain advantages over direct sequencing. For plants, there are several public GeneChip® arrays whose probes are localised primarily in 3′ exons. Plant whole-transcript (WT) GeneChip® arrays are not yet publicly available, although WT resolution is needed to study complex crop genomes such as Brassica, which are typified by segmental duplications containing paralogous genes and/or allopolyploidy. Available sequence data were sampled from the Brassica A and C genomes, and 142,997 gene models identified. The assembled gene models were then used to establish a comprehensive public WT exon array for transcriptomics studies. The Affymetrix GeneChip® Brassica Exon 1.0 ST Array is a 5 µM feature size array, containing 2.4 million 25-base oligonucleotide probes representing 135,201 gene
Biological & Technical Variation in Single Cell Gene Expression Experiments -Technical Note -Index -Single Cell Gene Expression...Biological & Technical Variation in Single Cell Gene Expression Experiments -Technical Note -Index -Single Cell Gene Expression...
CG000170_TechNote_BiologicalandTechnicalVariationinSingleCell3GeneExpressionExperiments_RevA_.pdf. Technical Note - Biological & Technical Variation in Single Cell Gene Expression Experiments. The Chromium Single Cell 3′ v2 Reagent Kits protocol (Document CG00052) produces Single Cell 3′ short-read sequencer compatible libraries. Technical and biological variation may be present in the experiment design, and may impact data interpretation. Potential sources of technical variation include running a sample on two separate microfluidic chips or at different well positions on the same chip, and or technical variation introduced by sequencing libraries on separate Illumina flowcells or sequencing lanes. This Technical Note examines the potential sources of technical and biological variation and their effects on single cell gene expression. These factors need to be considered when designing an experiment to minimize bias and generate reliable single cell gene expression data.. FOR USE WITH. ...
Data Mining for Genomics and Proteomics: Analysis of Gene and Protein Expression Data | Database & Data Warehousing...Data Mining for Genomics and Proteomics: Analysis of Gene and Protein Expression Data | Database & Data Warehousing...
Preface. Acknowledgments.. 1 Introduction.. 1.1 Basic Terminology.. 1.1.1 The Central Dogma of Molecular Biology.. 1.1.2 Genome.. 1.1.3 Proteome.. 1.1.4 DNA (Deoxyribonucleic Acid).. 1.1.5 RNA (Ribonucleic Acid).. 1.1.6 mRNA (messenger RNA).. 1.1.7 Genetic Code.. 1.1.8 Gene.. 1.1.9 Gene Expression and the Gene Expression Level.. 1.1.10 Protein.. 1.2 Overlapping Areas of Research.. 1.2.1 Genomics.. 1.2.2 Proteomics.. 1.2.3 Bioinformatics.. 1.2.4 Transcriptomics and Other -omics.. 1.2.5 Data Mining.. 2 Basic Analysis of Gene Expression Microarray Data.. 2.1 Introduction.. 2.2 Microarray Technology.. 2.2.1 Spotted Microarrays.. 2.2.2 Affymetrix GeneChip® Microarrays.. 2.2.3 Bead-Based Microarrays.. 2.3 Low-Level Preprocessing of Assymetrix Microarrays.. 2.3.1 MAS5.. 2.3.2 RMA.. 2.3.3 GCRMA.. 2.3.4 PLIER.. 2.4 Public Repositories of Microarray Data.. 2.4.1 Microarray Gene Expression Data Society (MGED) Standards.. 2.4.2 Public Databases.. 2.4.2.1 Gene Expression Omnibus (GEO).. 2.4.2.2 ...
Methodological study of affine transformations of gene expression data with proposed robust non-parametric multi-dimensional...Methodological study of affine transformations of gene expression data with proposed robust non-parametric multi-dimensional...
Methodological study of affine transformations of gene expression data with proposed robust non-parametric multi-dimensional normalization method - Background: Low-level processing and normalization of microarray data are most important steps in microarray analysis, which have profound impact on downstream analysis. Multiple methods have been suggested to date, but it is not clear which is the best. It is therefore important to further study the different normalization methods in detail and the nature of microarray data in general. Results: A methodological study of affine models for gene expression data is carried out. Focus is on two-channel comparative studies, but the findings generalize also to single- and multi-channel data. The discussion applies to spotted as well as in-situ synthesized microarray data. Existing normalization methods such as curve-fit (lowess) normalization, parallel and perpendicular translation normalization, and quantile normalization, but also dye-swap normalization are
Gene expression microarrays and their application in drought stress research. - GOV.UKGene expression microarrays and their application in drought stress research. - GOV.UK
Initial physiological adjustments in response to drought stress lead to drastic changes in gene expression. The traditional approaches of assessing such drought-induced changes in gene expression involve measuring the differences in mRNA levels of one or few genes at a time. DNA expression microarray technology is a powerful tool that can monitor changes in expression of a large number of genes simultaneously. Expression microarrays also provide new insights into physiological and biochemical pathways of drought tolerance, and thus can lead to identification of novel candidate genes that can rapidly advance breeding for drought tolerance. This review describes the basic principles and potential applications of gene expression microarrays in understanding and improving drought tolerance in plants. A case study is presented involving hybridization of field-grown panicle samples from drought tolerant and susceptible rice germplasm targets with probes from a normalized panicle cDNA library. Results ...
The Latent Process Decomposition of cDNA Microarray Data SetsThe Latent Process Decomposition of cDNA Microarray Data Sets
IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, VOL. 2, NO. 2, APRIL-JUNE 2005 1 The Latent Process Decomposition of cDNA Microarray Data Sets Simon Rogers, Mark Girolami, Colin Campbell, and Rainer Breitling Abstract-We present a new computational technique1 which enables the probabilistic analysis of cDNA microarray data and we demonstrate its effectiveness in identifying features of biomedical importance. A hierarchical Bayesian model, called Latent Process Decomposition (LPD), is introduced in which each sample in the data set is represented as a combinatorial mixture over a finite set of latent processes, which are expected to correspond to biological processes. Parameters in the model are estimated using efficient variational methods. This type of probabilistic model is most appropriate for the interpretation of measurement data generated by cDNA microarray technology. For determining informative substructure in such data sets, the proposed model has several important ...
A multi-fuzzy filtering approach to reliable gene expression profile analysisA multi-fuzzy filtering approach to reliable gene expression profile analysis
Seker, H. (2004) A Multi-Fuzzy Filtering Approach to Reliable Gene Expression Profile Analysis. Proceedings of the 2004 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, October 2004, pp. 37-40 ...
Transcription network construction for large-scale microarray datasets using a high-performance computing approach<...Transcription network construction for large-scale microarray datasets using a high-performance computing approach<...
TY - JOUR. T1 - Transcription network construction for large-scale microarray datasets using a high-performance computing approach. AU - Zhu, Mengxia Michelle. AU - Wu, Qishi. PY - 2008/3/4. Y1 - 2008/3/4. N2 - Background: The advance in high-throughput genomic technologies including microarrays has demonstrated the potential of generating a tremendous amount of gene expression data for the entire genome. Deciphering transcriptional networks that convey information on intracluster correlations and intercluster connections of genes is a crucial analysis task in the post-sequence era. Most of the existing analysis methods for genome-wide gene expression profiles consist of several steps that often require human involvement based on experiential knowledge that is generally difficult to acquire and formalize. Moreover, large-scale datasets typically incur prohibitively expensive computation overhead and thus result in a long experiment-analysis research cycle. Results: We propose a parallel ...
Differential gene expression patterns in developing sexually dimorphic rat brain regions exposed to antiandrogenic, estrogenic,...Differential gene expression patterns in developing sexually dimorphic rat brain regions exposed to antiandrogenic, estrogenic,...
Differential gene expression patterns in developing sexually dimorphic rat brain regions exposed to antiandrogenic, estrogenic, or complex endocrine disruptor mixtures: Glutamatergic synapses as ...
Gene expression profiling of meningiomas: current status after a decade of microarray-based transcriptomic studiesGene expression profiling of meningiomas: current status after a decade of microarray-based transcriptomic studies
Purpose This article provides a review of the transcriptomic expression profiling studies that have been performed on meningiomas so far. We discuss some future prospects and challenges ahead in the field of gene expression profiling. Methods We performed a systematic search in the PubMed and EMBASE databases in May 2010 using the following search terms alone or in combination: "meningioma", "microarray analysis", "oligonucleotide array sequence analysis", or "gene expression profiling". Only original research articles in English that had used RNA hybridized to high-resolution microarray chips to generate gene expression profiles were included. Results We identified 13 articles matching the inclusion criteria. All studies had been performed during the last decade. Conclusions The main results of the studies can be grouped in three categories: (1) several groups have identified meningioma-specific genes and genes associated with the three WHO grades, and the main histological subtypes of grade I ...
PSRC - Detection of Novel Cancer Subpopulations Through Integration of Public Microarray Data with Single Cell Gene Expression...PSRC - Detection of Novel Cancer Subpopulations Through Integration of Public Microarray Data with Single Cell Gene Expression...
A meta-analysis was performed across six public microarray datasets for human small cell lung cancer (SCLC) comprising 365 samples across eight different platforms. Genes were ranked according to effect size and p-value for tumor versus control samples, and false discovery rates were calculated. The top scoring 48 genes that were significant by both methods, along with the 48 highest rated surface antigen genes, were used to populate a gene list for subsequent single cell evaluation. High throughput gene expression analysis was performed for 400 individual cells from one SCLC line (H446) using the Fluidigm microfluidic platform. Supervised machine learning was applied to identify transcriptionally-defined subgroups among these cells. The non-parametric Kolmogorov-Smirnov test was then used to determine those surface markers best able to distinguish each cluster. Individual cells from each group were then FACS-isolated, and clonogenicity was evaluated after 14 days in culture. Using these surface ...
Differential gene expression profile reveals deregulation of pregnancy specific β1 glycoprotein 9 early during colorectal...Differential gene expression profile reveals deregulation of pregnancy specific β1 glycoprotein 9 early during colorectal...
APC (Adenomatous polyposis coli) plays an important role in the pathogenesis of both familial and sporadic colorectal cancer. Patients carrying germline APC mutations develop multiple colonic adenomas at younger age and higher frequency than non-carrier cases which indicates that silencing of one APC allele may be sufficient to initiate the transformation process. To elucidate the biological dysregulation underlying adenoma formation we examined global gene expression profiles of adenomas and corresponding normal mucosa from an FAP patient. Differential expression of the most significant gene identified in this study was further validated by mRNA in situ hybridization, reverse transcriptase PCR and Northern blotting in different sets of adenomas, tumours and cancer cell lines. Eighty four genes were differentially expressed between all adenomas and corresponding normal mucosa, while only seven genes showed differential expression within the adenomas. The first group included pregnancy specific β-1
Improved significance test for DNA microarray data: Temporal effects of shear stress on endothelial genes<...Improved significance test for DNA microarray data: Temporal effects of shear stress on endothelial genes<...
TY - JOUR. T1 - Improved significance test for DNA microarray data. T2 - Temporal effects of shear stress on endothelial genes. AU - Zhao, Yihua. AU - Chen, Benjamin P C. AU - Miao, Hui. AU - Yuan, Suli. AU - Li, Yi Shuan. AU - Hu, Yingli. AU - Rocke, David M. AU - Chien, Shu. PY - 2003/4. Y1 - 2003/4. N2 - Statistical methods for identifying differentially expressed genes from microarray data are evolving. We developed a test for the statistical significance of differential expression as a function of time. When applied to microarray data obtained from endothelial cells exposed to shearing for different durations, the new multi-group test (G-test) identified three times as many genes as the one-way ANOVA at the same significance level. Using simulated data, we showed that this increase in sensitivity was achieved without sacrificing specificity. Several genes known to respond to shear stress by Northern blotting were identified by the G-test at P ≤ 0.01 (but not by ANOVA), with similar ...
PLOS ONE: Functional Associations by Response Overlap (FARO), a Functional Genomics Approach Matching Gene Expression PhenotypesPLOS ONE: Functional Associations by Response Overlap (FARO), a Functional Genomics Approach Matching Gene Expression Phenotypes
The systematic comparison of transcriptional responses of organisms is a powerful tool in functional genomics. For example, mutants may be characterized by comparing their transcript profiles to those obtained in other experiments querying the effects on gene expression of many experimental factors including treatments, mutations and pathogen infections. Similarly, drugs may be discovered by the relationship between the transcript profiles effectuated or impacted by a candidate drug and by the target disease. The integration of such data enables systems biology to predict the interplay between experimental factors affecting a biological system. Unfortunately, direct comparisons of gene expression profiles obtained in independent, publicly available microarray experiments are typically compromised by substantial, experiment-specific biases. Here we suggest a novel yet conceptually simple approach for deriving Functional Association(s) by Response Overlap (FARO) between microarray gene expression
Analysing subsets of gene expression data to find putatively co-regulated genes - OpenThesisAnalysing subsets of gene expression data to find putatively co-regulated genes - OpenThesis
This project is an investigation of whether analysing subsets of time series gene expression data can give additional information about putatively co-regulated genes, compared to only using the whole time series. The original gene expression data set was partitioned into subsets and similarity was computed for both the whole timed series and subsets. Pearson correlation was used as similarity measure between gene expression profiles. The results indicate that analysing co-expression in subsets of gene expression data derives true-positive connections, with respect to co-regulation, that are not detected by only using the whole time series data. Unfortunately, with the actual data set, chosen similarity measure and partitioning of the data, randomly generated connections have the same amount of true-positives as the ones derived by the applied analysis. However, it is worth to continue further analysis of the subsets of gene expression data, which is based on the multi-factorial nature of gene ...
The effect of the CCR5-delta32 deletion on global gene expression consThe effect of the CCR5-delta32 deletion on global gene expression cons
... idering immune response and inflammation : The natural function of the C-C chemokine receptor type 5 (CCR5) is poorly understood. A 32 base pair deletion in the CCR5 gene (CCR5-delta32) located on chromosome 3 results in a non-functional protein. It is supposed that this deletion causes an alteration in T-cell response to inflammation. For example, the presence of the CCR5-delta32 allele in recipients of allografts constitutes as an
Comprehensive gene expression profiling and immunohistochemical studies support application of immunophenotypic algorithm for...Comprehensive gene expression profiling and immunohistochemical studies support application of immunophenotypic algorithm for...
TY - JOUR. T1 - Comprehensive gene expression profiling and immunohistochemical studies support application of immunophenotypic algorithm for molecular subtype classification in diffuse large B-cell lymphoma. T2 - A report from the International DLBCL Rituximab-CHOP Consortium Program Study. AU - Visco, C.. AU - Li, Y.. AU - Xu-Monette, Z. Y.. AU - Miranda, R. N.. AU - Green, T. M.. AU - Li, Y.. AU - Tzankov, A.. AU - Wen, W.. AU - Liu, W. M.. AU - Kahl, B. S.. AU - DAmore, E. S.G.. AU - Montes-Moreno, S.. AU - Dybkær, K.. AU - Chiu, A.. AU - Tam, W.. AU - Orazi, A.. AU - Zu, Y.. AU - Bhagat, G.. AU - Winter, J. N.. AU - Wang, H. Y.. AU - ONeill, S.. AU - Dunphy, C. H.. AU - Hsi, E. D.. AU - Zhao, X. F.. AU - Go, R. S.. AU - Choi, W. W.L.. AU - Zhou, F.. AU - Czader, M.. AU - Tong, J.. AU - Zhao, X.. AU - Van Krieken, J. H.. AU - Huang, Q.. AU - Ai, W.. AU - Etzell, J.. AU - Ponzoni, M.. AU - Ferreri, A. J.M.. AU - Piris, M. A.. AU - Møller, M. B.. AU - Bueso-Ramos, C. E.. AU - Medeiros, L. ...
Comprehensive gene expression profiling and immunohistochemical studies support application of immunophenotypic algorithm for...Comprehensive gene expression profiling and immunohistochemical studies support application of immunophenotypic algorithm for...
Comprehensive gene expression profiling and immunohistochemical studies support application of immunophenotypic algorithm for molecular subtype classification in diffuse large B-cell lymphoma: a report from the International DLBCL Rituximab-CHOP Consortium Program Study.
Classification and Biomarker Genes Selection for Cancer Gene Expression Data Using Random ForestClassification and Biomarker Genes Selection for Cancer Gene Expression Data Using Random Forest
Background & objective: Microarray and next generation sequencing (NGS) data are the important sources to find helpful molecular patterns. Also, the great number of gene expression data increases the challenge of how to identify the biomarkers associated with cancer. The random forest (RF) is used to effectively analyze the problems of large-p and small-n. Therefore, RF can be used to select and rank the genes for the diagnosis and effective treatment of cancer. Methods: The microarray gene expression data of colon, leukemia, and prostate cancers were collected from public databases. Primary preprocessing was done on them using limma package, and then, the RF classification method was implemented on datasets separately in R software. Finally, the selected genes in each of the cancers were evaluated and compared with those of previous experimental studies and their functionalities were assessed in molecular cancer processes. Result: The RF method extracted very small sets of genes while it retained its
Background Gene expression microarrays permit the quantification of transcript accumulation for - Gremlin is a Key Pro...Background Gene expression microarrays permit the quantification of transcript accumulation for - Gremlin is a Key Pro...
Background Gene expression microarrays permit the quantification of transcript accumulation for most or all genes within a genome. increasing this process, we could actually identify eQTLs managing network replies for 18 out of 20 a priori-described gene networks within a recombinant inbred series population produced from accessions Bay-0 and Shahdara. Bottom line This approach gets the potential to become expanded to assist in direct exams of the ACP-196 manufacture partnership between phenotypic characteristic and transcript hereditary architecture. The usage of a priori explanations for network eQTL id has enormous prospect of providing path toward upcoming eQTL analyses. History Many phenotypic characteristics, ranging from disease susceptibility to development, are quantitative in nature and are analyzed in both animals and plants via quantitative trait locus (QTL) mapping [1-3]. QTLs are regions of the genome associated with phenotypic variance for a trait. These regions may or may not ...
Report on emerging technologies for translational bioinformatics: a symposium on gene expression profiling for archival tissues...Report on emerging technologies for translational bioinformatics: a symposium on gene expression profiling for archival tissues...
Report on emerging technologies for translational bioinformatics: a symposium on gene expression profiling for archival tissues. . Biblioteca virtual para leer y descargar libros, documentos, trabajos y tesis universitarias en PDF. Material universiario, documentación y tareas realizadas por universitarios en nuestra biblioteca. Para descargar gratis y para leer online.
Critical Appraisal of DNA Microarrays in Psychiatric Genomics<...Critical Appraisal of DNA Microarrays in Psychiatric Genomics<...
TY - JOUR. T1 - Critical Appraisal of DNA Microarrays in Psychiatric Genomics. AU - Mirnics, Károly. AU - Levitt, Pat. AU - Lewis, David A.. PY - 2006/7/15. Y1 - 2006/7/15. N2 - Transcriptome profiling using DNA microarrays are data-driven approaches with the potential to uncover unanticipated relationships between gene expression alterations and psychiatric disorders. Studies to date have yielded both convergent and divergent findings. Differences may be explained, at least in part, by the use of a variety of microarray platforms and analytical approaches. Consistent findings across studies suggest, however, that important relationships may exist between altered gene expression and genetic susceptibility to psychiatric disorders. For example, GAD67, RGS4, DTNBP1, NRG1, and GABRAB2 show expression alterations in the postmortem brain of subjects with schizophrenia, and these genes have been also implicated as putative, heritable schizophrenia susceptibility genes. Thus, we propose that for some ...
A Decade of Global mRNA and miRNA Profiling of HPV-Positive Cell Lines and Clinical Specimens [Abstract]A Decade of Global mRNA and miRNA Profiling of HPV-Positive Cell Lines and Clinical Specimens [Abstract]
For more than a decade, global gene expression profiling has been extensively used to elucidate the biology of human papillomaviruses (HPV) and their role in cervical- and head-and-neck cancers. Since 2008, the expression profiling of miRNAs has been reported in multiple HPV studies. Two major strategies have been employed in the gene and miRNA profiling studies: In the first approach, HPV positive tumors were compared to normal tissues or to HPV negative tumors. The second strategy relied on analysis of cell cultures transfected with single HPV oncogenes or with HPV genomes compared to untransfected cells considered as models for the development of premalignant and malignant transformations.. In this review, we summarize what we have learned from a decade of global expression profiling studies. We performed comprehensive analysis of the overlap of the lists of differentially expressed genes and microRNAs, in both tissue samples and cell culture based studies. The review focuses mainly on HPV16, ...
A Razor May Be Sharper Than an Ax, but It Cannot Cut Wood | Anesthesiology | ASA Publications"A Razor May Be Sharper Than an Ax, but It Cannot Cut Wood" | Anesthesiology | ASA Publications
Because microarray experiments literally involve the comparison of thousands of data points, the scientific community has grappled with identifying specific guidelines for the conductance, statistical analysis, and interpretation of microarray experiments due to the significant potential for false positives (i.e. , type I error). To this end, the Microarray Gene Expression Data Society, an international organization of molecular biologists, computer scientists, and data analysts, developed standards known as the Minimum Information About a Microarray Experiment (MIAME), which outlines the minimum information that should be reported about a microarray experiment to enable its unambiguous interpretation and reproduction.5 1In addition adhering to the MIAME guidelines, Lucchinetti et al. analyzed their microarray data using a highly sophisticated technique known as gene set enrichment analysis. Gene set enrichment analysis is a computational method that determines whether an a priori defined set of ...
JPM | Free Full-Text | Clinical Utility of Gene Expression Profiling Data for Clinical Decision-Making Regarding Adjuvant...JPM | Free Full-Text | Clinical Utility of Gene Expression Profiling Data for Clinical Decision-Making Regarding Adjuvant...
Breast cancer is the most common malignancy among women in the United States with the second highest incidence of cancer-related death following lung cancer. The decision-making process regarding adjuvant therapy is a time intensive dialogue between the patient and her oncologist. There are multiple tools that help individualize the treatment options for a patient. Population-based analysis with Adjuvant! Online and genomic profiling with Oncotype DX are two commonly used tools in patients with early stage, node-negative breast cancer. This case report illustrates a situation in which the population-based prognostic and predictive information differed dramatically from that obtained from genomic profiling and affected the patients decision. In light of this case, we discuss the benefits and limitations of these tools.
FARO server: Meta-analysis of gene expression by matching gene expression signatures to a compendium of public gene expression...FARO server: Meta-analysis of gene expression by matching gene expression signatures to a compendium of public gene expression...
BACKGROUND: Although, systematic analysis of gene annotation is a powerful tool for interpreting gene expression data, it sometimes is blurred by incomplete gene annotation, missing expression response of key genes and secondary gene expression responses. These shortcomings may be partially circumvented by instead matching gene expression signatures to signatures of other experiments. FINDINGS: To facilitate this we present the Functional Association Response by Overlap (FARO) server, that match input signatures to a compendium of 242 gene expression signatures, extracted from more than 1700 Arabidopsis microarray experiments. CONCLUSIONS: Hereby we present a publicly available tool for robust characterization of Arabidopsis gene expression experiments which can point to similar experimental factors in other experiments. The server is available at http://www.cbs.dtu.dk/services/faro ...
Plus itPlus it
We did a genome-wide transcription profiling study of 60 children, with first relapse of ALL enrolled in the relapse trial ALL-REZ BFM 2002 of the BFM study group. Genetic and immunologic subclasses described by gene expression profiling studies of initial ALL (10, 12) were correctly predicted from microarray data in relapse patients, thus proving consistency of microarray-based leukemia subtype classification across different stages of disease. To identify molecular determinants of the major prognostic factors at ALL relapse, we compared prognostic groups of B-cell precursor ALL relapse classified according to each of these factors. No significant gene expression patterns were found to correlate with the prognostic factors site of relapse and MRD. About the most evident prognostic factor time of relapse, we identified significant differences in gene expression between patients with very early and late relapse. We obtained a list of 83 differentially expressed genes mostly up-regulated in very ...
Candidate Agtr2 influenced genes and pathways identified by expression profiling in the developing brain of Agtr2(-/y) mice |...Candidate Agtr2 influenced genes and pathways identified by expression profiling in the developing brain of Agtr2(-/y) mice |...
Intellectual disability (ID) is a common developmental disability observed in 1 to 3% of the human population. A possible role for the Angiotensin II type 2 receptor (AGTR2) in brain function, affecting learning, memory, and behavior, has been suggested in humans and rodents. Mice lacking the Agtr2 gene (Agtr2(-/y)) showed significant impairment in their spatial memory and exhibited abnormal dendritic spine morphology. To identify Agtr2 influenced genes and pathways, we performed whole genome microarray analysis on RNA isolated from brains of Agtr2(-/y) and control male mice at embryonic day 15 (E15) and postnatal day one (P1). The gene expression profiles of the Agtr2(-/y) brain samples were significantly different when compared to profiles of the age-matched control brains. We identified 62 differently expressed genes (p, or =0.005) at E15 and in P1 brains of the Agtr2(-/y) mice. We verified the differential expression of several of these genes in brain samples using quantitative RT-PCR. ...
Distinct gene expression profiles in subsets of chronic lymphocytic leukemia expressing stereotyped IGHV4-34 B-cell receptors |...Distinct gene expression profiles in subsets of chronic lymphocytic leukemia expressing stereotyped IGHV4-34 B-cell receptors |...
In the present study, we examined the gene expression profile of 25 IGHV4-34 patients including subset #4, #16 and non-subset 4/16 cases. Initially, we compared the gene expression profiles between subset #4 and non-subset 4/16 patients and between subset #16 patients and non-subset 4/16 patients, and detected only few significant differences. This is probably because, overall, non-subset 4/16 IGHV4-34 cases exhibited a more heterogeneous gene expression profile, likely reflecting the structural heterogeneity of their BCR, which would be expected to be responsive to a far wider range of antigens than that recognized by stereotyped subsets. Interestingly, however, we detected distinct differences in gene expression patterns when comparing subset #4 and #16 cases, both of which can be reliably defined at the molecular level based on subset-specific VH CDR3 and subset-biased features of somatic hypermutation.8 This finding is supported by the recent observation that stereotyped subset cases have ...
DNA microarrayDNA microarray
BiochipBiochip
Oligonucleotide synthesisOligonucleotide synthesis
Biokiip - VikipeediaBiokiip - Vikipeedia
Bayesian tool for methylation analysisBayesian tool for methylation analysis
File:Neighbor-joining Tree.svgFile:Neighbor-joining Tree.svg
Association of Biomolecular Resource FacilitiesAssociation of Biomolecular Resource Facilities
Gene expression profiling in cancerGene expression profiling in cancer
FlexGenFlexGen
Representational difference analysisRepresentational difference analysis
OLIGO Primer Analysis SoftwareOLIGO Primer Analysis Software
BRCA1BRCA1
Molecular biologyMolecular biology
Extracellular RNAExtracellular RNA
OncogenomicsOncogenomics
FnrS RNAFnrS RNA
Suspension array technologySuspension array technology
Beijing Genomics InstituteBeijing Genomics Institute
Leroy HoodLeroy Hood
Escherichia coli sRNAEscherichia coli sRNA
Annexin A7Annexin A7
Transcriptomics technologiesTranscriptomics technologies
SNP arraySNP array
Glossary of gene expression termsGlossary of gene expression terms
BioinformaticsBioinformatics
ChIP-sequencingChIP-sequencing
Gene expressionGene expression
Comparative genomic hybridizationComparative genomic hybridization
Medical geneticsMedical genetics
Fluorescence in situ hybridizationFluorescence in situ hybridization
Surface-enhanced Raman spectroscopySurface-enhanced Raman spectroscopy
Single cell sequencingSingle cell sequencing
DNA sequencingDNA sequencing
Organic chemistryOrganic chemistry
Serial analysis of gene expressionSerial analysis of gene expression
GenomicsGenomics
Drug designDrug design
DNADNA
Bio-MEMSBio-MEMS
권성훈 - 위키백과, 우리 모두의 백과사전권성훈 - 위키백과, 우리 모두의 백과사전
Circulating tumor cellCirculating tumor cell
Gene expression profilingGene expression profiling
Tiling arrayTiling array
Virtual karyotypeVirtual karyotype
Reverse transcription polymerase chain reactionReverse transcription polymerase chain reaction
DNA-binding domainDNA-binding domain
MicroRNAMicroRNA
Massive parallel sequencingMassive parallel sequencing
Multiple displacement amplificationMultiple displacement amplification
Genome editingGenome editing
Edwin SouthernEdwin Southern
AnatomyOrganismsDiseasesChemicals and DrugsAnalytical, Diagnostic and Therapeutic Techniques and EquipmentPsychiatry and PsychologyPhenomena and ProcessesDisciplines and OccupationsTechnology, Industry, AgricultureInformation ScienceHealth Care
Oligonucleotide Array Sequence AnalysisOligonucleotide ProbesGene Expression ProfilingSequence Analysis, DNAOligonucleotidesBase SequenceMolecular Sequence DataNucleic Acid HybridizationDNA ProbesComparative Genomic HybridizationPolymerase Chain ReactionAmino Acid SequenceReproducibility of ResultsDNA, Ribosomal SpacerGene DosageRNA, MessengerReverse Transcriptase Polymerase Chain ReactionSensitivity and SpecificityCluster AnalysisDNAAlgorithmsDNA, BacterialCloning, MolecularOligonucleotides, AntisenseGenome, HumanSequence AnalysisRNATranscription, GeneticGene Expression RegulationDNA PrimersPhylogenyChromosome MappingSpecies SpecificityGene ExpressionChromosomes, Artificial, BacterialIn Situ Hybridization, FluorescenceRNA, ComplementaryRNA, Ribosomal, 16SGlassSequence Homology, Nucleic AcidMicroarray AnalysisFixativesGene Expression Regulation, NeoplasticDNA, ComplementaryOligodeoxyribonucleotidesExonsMutationGenetic VariationModels, GeneticDNA Copy Number VariationsPolymorphism, Single NucleotideSoftwareDNA, RibosomalMultigene FamilyComputational BiologyGenomicsGenotypeNucleic Acid Amplification TechniquesExpressed Sequence TagsTranscription FactorsModels, StatisticalData Interpretation, StatisticalSequence Homology, Amino AcidRNA, NeoplasmGenes, NeoplasmChromosome AberrationsGenes, BacterialSequence AlignmentAllelesDNA-Binding ProteinsBlotting, NorthernReference StandardsRestriction MappingCell LineDNA Mutational AnalysisGene DeletionPhenotypePromoter Regions, GeneticGenomeOligoribonucleotidesDatabases, GeneticCelastraceaeUp-RegulationEscherichia coliBase CompositionGenome, PlantGene DuplicationNucleic Acid ConformationCell Line, TumorTumor Cells, CulturedBacterial ProteinsRNA, BacterialAptitudePlasmidsComputer SimulationProteinsDNA, NeoplasmPhosphorothioate OligonucleotidesOpen Reading FramesOligodeoxyribonucleotides, AntisenseProtein Array AnalysisSignal TransductionNeoplasm ProteinsGenesGene LibraryCells, CulturedBlotting, SouthernGenes, rRNABinding SitesDown-RegulationBacterial Typing TechniquesSequence Analysis, ProteinTime FactorsRepetitive Sequences, Nucleic AcidDNA, ViralThionucleotidesElectrophoresis, Polyacrylamide GelDNA Restriction EnzymesApoptosisDNA, FungalRNA, ViralOligoribonucleotides, AntisenseMice, Inbred C57BLMolecular WeightConserved SequenceCodonGenes, ViralRecombinant ProteinsSequence HomologyKineticsPolymorphism, Restriction Fragment LengthSequence Analysis, RNACattleMolecular Probe TechniquesNucleic Acid DenaturationSubstrate SpecificitySoil MicrobiologyBacteriaDNA Transposable ElementsRNA, RibosomalGenome, ViralChromatography, High Pressure LiquidEvolution, MolecularProtein BindingConsensus SequenceIntrons
Oligonucleotide Array Sequence Analysis (Topic) - Rensselaer LibrariesOligonucleotide Array Sequence Analysis (Topic) - Rensselaer Libraries
Light-generated oligonucleotide arrays for rapid DNA sequence analysis | PNASLight-generated oligonucleotide arrays for rapid DNA sequence analysis | PNAS
Oligonucleotide Array Sequence Analysis | Antimicrobial Agents and ChemotherapyOligonucleotide Array Sequence Analysis | Antimicrobial Agents and Chemotherapy
Oligonucleotide Array Sequence Analysis | ISHAR OnlineOligonucleotide Array Sequence Analysis | ISHAR Online
Oligonucleotide Array Sequence Analysis | Colorado PROFILESOligonucleotide Array Sequence Analysis | Colorado PROFILES
Oligonucleotide Array Sequence Analysis | Profiles RNSOligonucleotide Array Sequence Analysis | Profiles RNS
Oligonucleotide Array Sequence Analysis (Concept) - Deakin University LibraryOligonucleotide Array Sequence Analysis (Concept) - Deakin University Library
Solution hybrid selection with ultra-long oligonucleotides for massively parallel targeted sequencingSolution hybrid selection with ultra-long oligonucleotides for massively parallel targeted sequencing
Identification of genes regulated by dexamethasone in multiple myeloma cells using oligonucleotide arraysIdentification of genes regulated by dexamethasone in multiple myeloma cells using oligonucleotide arrays
Influence of age, sex, and strength train... & related info | MendeleyInfluence of age, sex, and strength train... & related info | Mendeley
Patent US6315958 - Flow cell for synthesis of arrays of DNA probes and the like - Google PatentsPatent US6315958 - Flow cell for synthesis of arrays of DNA probes and the like - Google Patents
Rhabdomyosarcoma | Cancer Genetics WebRhabdomyosarcoma | Cancer Genetics Web
CD27 | Cancer Genetics WebCD27 | Cancer Genetics Web
Signature microRNA expression profile of essential hypertension and its novel link to human cytomegalovirus infection.Signature microRNA expression profile of essential hypertension and its novel link to human cytomegalovirus infection.
Identificação de fatores diabetogênicos associados ao adenocarcinoma de pâncreasIdentificação de fatores diabetogênicos associados ao adenocarcinoma de pâncreas
The effect of prior assumptions over the weights in BayesPI with application to study protein-DNA interactions from ChIP-based...The effect of prior assumptions over the weights in BayesPI with application to study protein-DNA interactions from ChIP-based...
Erlotinib Before and After Surgery in Treating Patients With Muscle-Invasive Bladder CancerErlotinib Before and After Surgery in Treating Patients With Muscle-Invasive Bladder Cancer
Avaliação do transcriptoma e proteoma de células de câncer de mama com diferente...Avaliação do transcriptoma e proteoma de células de câncer de mama com diferente...
Patente US6428752 - Cleaning deposit devices that form microarrays and the like - Google PatentesPatente US6428752 - Cleaning deposit devices that form microarrays and the like - Google Patentes
Christopher Woelk | Woelk lab | University of SouthamptonChristopher Woelk | Woelk lab | University of Southampton
Setlur S[au] - PubMed - NCBISetlur S[au] - PubMed - NCBI
Mette Lübeck - Fingerprint - Aalborg Universitys Research PortalMette Lübeck - Fingerprint - Aalborg University's Research Portal
Antibody Colocalization Microarray: A Scalable Technology for Multiplex Protein Analysis in Complex Samples | Molecular &...Antibody Colocalization Microarray: A Scalable Technology for Multiplex Protein Analysis in Complex Samples | Molecular &...
Patent US6262216 - Functionalized silicon compounds and methods for their synthesis and use - Google PatentsPatent US6262216 - Functionalized silicon compounds and methods for their synthesis and use - Google Patents
Design of oligonucleotides for microarrays and perspectives for design of multi-transcriptome arrays<...Design of oligonucleotides for microarrays and perspectives for design of multi-transcriptome arrays<...
Academic Programs Faculty - Last Initial L - Wake Forest School of MedicineAcademic Programs Faculty - Last Initial L - Wake Forest School of Medicine
Reverse engineering and analysis of genome-wide gene regulatory networks from gene expression profiles using high-performance...Reverse engineering and analysis of genome-wide gene regulatory networks from gene expression profiles using high-performance...
Molecular characterization of schizophrenia viewed by microarray analysis of gene expression in prefrontal cortex. | CureHunterMolecular characterization of schizophrenia viewed by microarray analysis of gene expression in prefrontal cortex. | CureHunter
The Role of Epigenetic Modifications in Autism Spectrum DisorderThe Role of Epigenetic Modifications in Autism Spectrum Disorder
Analysis of lymphoblastic lymphoma cells from Stat5 tra | Open-iAnalysis of lymphoblastic lymphoma cells from Stat5 tra | Open-i
AnatomyOrganismsDiseasesChemicals and DrugsAnalytical, Diagnostic and Therapeutic Techniques and EquipmentPsychiatry and PsychologyPhenomena and ProcessesDisciplines and OccupationsTechnology, Industry, AgricultureInformation ScienceHealth Care
Oligonucleotide Array Sequence AnalysisOligonucleotide ProbesGene Expression ProfilingSequence Analysis, DNAOligonucleotidesBase SequenceMolecular Sequence DataNucleic Acid HybridizationDNA ProbesComparative Genomic HybridizationPolymerase Chain ReactionAmino Acid SequenceReproducibility of ResultsDNA, Ribosomal SpacerGene DosageRNA, MessengerReverse Transcriptase Polymerase Chain ReactionSensitivity and SpecificityCluster AnalysisDNAAlgorithmsDNA, BacterialCloning, MolecularOligonucleotides, AntisenseGenome, HumanSequence AnalysisRNATranscription, GeneticGene Expression RegulationDNA PrimersPhylogenyChromosome MappingSpecies SpecificityGene ExpressionChromosomes, Artificial, BacterialIn Situ Hybridization, FluorescenceRNA, ComplementaryRNA, Ribosomal, 16SGlassSequence Homology, Nucleic AcidMicroarray AnalysisFixativesGene Expression Regulation, NeoplasticDNA, ComplementaryOligodeoxyribonucleotidesExonsMutationGenetic VariationModels, GeneticDNA Copy Number VariationsPolymorphism, Single NucleotideSoftwareDNA, RibosomalMultigene FamilyComputational BiologyGenomicsGenotypeNucleic Acid Amplification TechniquesExpressed Sequence TagsTranscription FactorsModels, StatisticalData Interpretation, StatisticalSequence Homology, Amino AcidRNA, NeoplasmGenes, NeoplasmChromosome AberrationsGenes, BacterialSequence AlignmentAllelesDNA-Binding ProteinsBlotting, NorthernReference StandardsRestriction MappingCell LineDNA Mutational AnalysisGene DeletionPhenotypePromoter Regions, GeneticGenomeOligoribonucleotidesDatabases, GeneticCelastraceaeUp-RegulationEscherichia coliBase CompositionGenome, PlantGene DuplicationNucleic Acid ConformationCell Line, TumorTumor Cells, CulturedBacterial ProteinsRNA, BacterialAptitudePlasmidsComputer SimulationProteinsDNA, NeoplasmPhosphorothioate OligonucleotidesOpen Reading FramesOligodeoxyribonucleotides, AntisenseProtein Array AnalysisSignal TransductionNeoplasm ProteinsGenesGene LibraryCells, CulturedBlotting, SouthernGenes, rRNABinding SitesDown-RegulationBacterial Typing TechniquesSequence Analysis, ProteinTime FactorsRepetitive Sequences, Nucleic AcidDNA, ViralThionucleotidesElectrophoresis, Polyacrylamide GelDNA Restriction EnzymesApoptosisDNA, FungalRNA, ViralOligoribonucleotides, AntisenseMice, Inbred C57BLMolecular WeightConserved SequenceCodonGenes, ViralRecombinant ProteinsSequence HomologyKineticsPolymorphism, Restriction Fragment LengthSequence Analysis, RNACattleMolecular Probe TechniquesNucleic Acid DenaturationSubstrate SpecificitySoil MicrobiologyBacteriaDNA Transposable ElementsRNA, RibosomalGenome, ViralChromatography, High Pressure LiquidEvolution, MolecularProtein BindingConsensus SequenceIntrons
MicroarraysGenesCDNAProbesWhole genomeBioinformaticsGenomicsDetectionBiologicalExpressionDeletionsAntibodiesNext-generationDataMethods10,000MicroarrayPolymerase Chain ReProfilingGenomeGeneticsProteinsHigh densityTranscriptomePhenotypeMass SpectrometrySynthetic oligonucleotidesImmunohistochemistryDatasetsNucleotideChromosomesProteomicTarget nucleic acidPOLYNUCLEOTIDE SEQUENCESPathologicCluster AnalysisGenomesU133AMeSHAffymetrixMethodsSensitivityClinical
Microarrays1
Genes6
CDNA1
Probes3
  • Specifically for oligonucleotide arrays, such as Affymetrix GeneChip®, multiple probes are associated with each target paired as perfect match (PM) probes, designed to capture specific binding and mismatch (MM) probes, designed to capture non-specific binding. (sheffield.ac.uk)
  • These were investigated with either OGT's exon targeted CytoSure Constitutional v3 array, based on up-to-date content from the Deciphering Developmental Disorders (DDD) study and ClinGen (Clinical Genome Resource), or a conventional array design based on content from the ISCA (International Standards for Cytogenomic Arrays) consortium with a large number of backbone probes and gene coverage based on an earlier version DD/ID databases. (cambridgesciencepark.co.uk)
  • The participating groups were provided with identical lists of microarray probes, including test statistics for three different contrasts, and the normalised log-ratios for each array, to be used as the starting point for interpreting the affected probes. (biomedcentral.com)
Whole genome1
Bioinformatics2
Genomics2
Detection3
  • In a recent, prominent, npj Genomic Medicine paper, Oxford Gene Technology's (OGT - A Sysmex Group Company) CytoSure™ Constitutional v3 array design has been shown to significantly improve reporting rate and been proven as a powerful tool for detection of small pathogenic intragenic deletions and duplications in developmental disorder (DD) research. (cambridgesciencepark.co.uk)
  • The paper, titled 'Exon-focused targeted oligonucleotide microarray design increases detection of clinically relevant variants across multiple NHS genomic centres' was led by a consortium of NHS genomic medicine centres in the UK and compared the enhanced exon-level gene coverage of the v3 array to a conventional array design. (cambridgesciencepark.co.uk)
  • Our results show that this array design leads to a significant improvement in reporting rate and provides a powerful tool for detection of small pathogenic intragenic deletions and duplications in the clinical setting. (cambridgesciencepark.co.uk)
Biological3
Expression3
Deletions1
Antibodies1
Next-generation2
  • I am currently working to extend the use of probabilistic models to Next Generation Sequencing data, with particular focus on de-novo isoforms identification and data integration. (sheffield.ac.uk)
  • This research is done in close collaboration with the PUMA project to extend it to Next Generation Sequencing (NGS) data applications. (sheffield.ac.uk)
Data2
  • Emma Shipstone, Executive VP Marketing, commented "We're delighted with this publication as it validates what we've always known about the performance of our CytoSure Constitutional v3 array and the quality of the data-it's great to see that crystallised in this research. (cambridgesciencepark.co.uk)
  • The aim of the workshop was to evaluate and present existing methods and softwares, and potentially to propose new methods to deal with the post-analyses of microarray data, using real data sourced from within EADGENE and SABRE. (biomedcentral.com)
Methods1
10,0001
Microarray18
Polymerase Chain Re1
  • We based candidate gene selection on bioinformatics, reverse transcription-polymerase chain reaction (RT-PCR), bisulfite sequencing, methylation-specific PCR and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. (uni-regensburg.de)
Profiling3
Genome12
Genetics2
Proteins3
  • Mass spectrometry is a powerful technology for the analysis of large numbers of endogenous proteins. (ku.dk)
  • Our analysis spans more than four orders of magnitude in protein abundance with no discrimination against membrane or low level regulatory proteins. (ku.dk)
  • Using a quantitative analysis of mRNA and protein expression within the same lung adenocarcinomas, we showed that only a subset of the proteins exhibited a significant correlation with mRNA abundance. (mcponline.org)
High density2
Transcriptome1
  • Based on structural tissue analyses and transcriptome data, we showed that early correction of diabetes attenuated and even prevented pathological changes in the eye, kidney, liver and aorta. (nus.edu.sg)
Phenotype1
  • Emerging genetic sequence data and phenotype association studies are expected to enable disease risk prediction and guide subsequent therapeutic approaches in individual cases. (aspetjournals.org)
Mass Spectrometry1
Synthetic oligonucleotides2
Immunohistochemistry1
  • Tumor tissue is obtained at baseline (at the original or confirmatory transurethral resection of the bladder tumor) and at the time of cystectomy for analysis of drug-specific and tissue-based biomarkers by western blot, immunohistochemistry, and gene array techniques. (bioportfolio.com)
Datasets1
  • The expression and prognostic value of alanine-glyoxylate and serine-pyruvate aminotransferase (AGXT) was further evaluated in HCC datasets in Oncomine and an independent HCC tissue array cohort. (springer.com)
Nucleotide6
Chromosomes1
  • The results from the array studies highlighted the complexity of rearrangements of chromosome 22 compared with the low frequency of alterations involving the other chromosomes. (aacrjournals.org)
Proteomic1
  • By combining proteomic and transcriptional analyses of the same samples, however, it may be possible to understand the complex mechanisms influencing protein expression in human cancer. (mcponline.org)
Target nucleic acid4
POLYNUCLEOTIDE SEQUENCES1
Pathologic1
  • Combined data from OA's expression array and function prediction data suggest that OA might play a role in several pathologic conditions, including hypertension, diabetes, and immune system disorders. (medscimonit.com)
Cluster Analysis2
  • Hierarchical cluster analysis clearly distinguished between benign and malignant tissue and between squamous cell carcinomas and adenocarcinomas. (uni-regensburg.de)
  • Finally, hierarchical cluster analysis revealed that the repeated samples clustered together regardless of the laboratory in which the experiments were done. (elsevier.com)
Genomes2
  • This project will develop methods to utilize new highly parallel DNA sequencing platforms to investigate structural variations in the genomes of cancer cells. (genome.gov)
  • Next-generation sequencing technologies are now being exploited not only to analyse static genomes, but also dynamic transcriptomes in an approach termed RNA-seq. (ucl.ac.uk)
U133A1
  • Gene expression in surgically resected and microdissected samples of non-small-cell lung cancers (18 squamous cell carcinomas and nine adenocarcinomas), matched normal bronchial epithelium, and peripheral lung tissue from both smokers (n = 22) and non-smokers (n = 5) was studied using the Affymetrix U133A array. (uni-regensburg.de)
MeSH2
  • Oligonucleotide Array Sequence Analysis" is a descriptor in the National Library of Medicine's controlled vocabulary thesaurus, MeSH (Medical Subject Headings) . (ucdenver.edu)
  • 0https://id.nlm.nih.gov/mesh/ D020869 650 22 Oligonucleotide Array Sequence Analysis. (opal-libraries.org)
Affymetrix1
Methods4
Sensitivity2
Clinical1
  • This chapter covers amplified- and nonamplified-probe techniques, postamplification detection and analysis, clinical applications of these techniques. (asmscience.org)